Ubiquitous and Pervasive Computing: Concepts, Methodologies, Tools, and Applications

Ubiquitous and Pervasive Computing: Concepts, Methodologies, Tools, and Applications Judith Symonds Auckland University of Technology, New Zealand

Volume I

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Published in the United States of America by Information Science Reference (an imprint of IGI Global) 701 E. Chocolate Avenue Hershey PA 17033 Tel: 717-533-8845 Fax: 717-533-8661 E-mail: [email protected] Web site: http://www.igi-global.com/reference and in the United Kingdom by Information Science Reference (an imprint of IGI Global) 3 Henrietta Street Covent Garden London WC2E 8LU Tel: 44 20 7240 0856 Fax: 44 20 7379 0609 Web site: http://www.eurospanbookstore.com Copyright © 2010 by IGI Global. All rights reserved. No part of this publication may be reproduced, stored or distributed in any form or by any means, electronic or mechanical, including photocopying, without written permission from the publisher. Product or company names used in this set are for identification purposes only. Inclusion of the names of the products or companies does not indicate a claim of ownership by IGI Global of the trademark or registered trademark. Library of Congress Cataloging-in-Publication Data Ubiquitous and pervasive computing : concepts, methodologies, tools, and applications / Judith Symonds, editor. p. cm. Includes bibliographical references and index. Summary: "This publication covers the latest innovative research findings involved with the incorporation of technologies into everyday aspects of life"--Provided by publisher. ISBN 978-1-60566-960-1 (hardcover) -- ISBN 978-1-60566-961-8 (ebook) 1. Ubiquitous computing. I. Symonds, Judith, 1972QA76.5915.U2565 2009 004--dc22 2009031090

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Editor-in-Chief Mehdi Khosrow-Pour, DBA Editor-in-Chief Contemporary Research in Information Science and Technology, Book Series

Associate Editors Steve Clarke University of Hull, UK Murray E. Jennex San Diego State University, USA Annie Becker Florida Institute of Technology USA Ari-Veikko Anttiroiko University of Tampere, Finland

Editorial Advisory Board Sherif Kamel American University in Cairo, Egypt In Lee Western Illinois University, USA Jerzy Kisielnicki Warsaw University, Poland Keng Siau University of Nebraska-Lincoln, USA Amar Gupta Arizona University, USA Craig van Slyke University of Central Florida, USA John Wang Montclair State University, USA Vishanth Weerakkody Brunel University, UK

Additional Research Collections found in the “Contemporary Research in Information Science and Technology” Book Series Data Mining and Warehousing: Concepts, Methodologies, Tools, and Applications John Wang, Montclair University, USA • 6-volume set • ISBN 978-1-60566-056-1 Electronic Business: Concepts, Methodologies, Tools, and Applications In Lee, Western Illinois University • 4-volume set • ISBN 978-1-59904-943-4 Electronic Commerce: Concepts, Methodologies, Tools, and Applications S. Ann Becker, Florida Institute of Technology, USA • 4-volume set • ISBN 978-1-59904-943-4 Electronic Government: Concepts, Methodologies, Tools, and Applications Ari-Veikko Anttiroiko, University of Tampere, Finland • 6-volume set • ISBN 978-1-59904-947-2 Knowledge Management: Concepts, Methodologies, Tools, and Applications Murray E. Jennex, San Diego State University, USA • 6-volume set • ISBN 978-1-59904-933-5 Information Communication Technologies: Concepts, Methodologies, Tools, and Applications Craig Van Slyke, University of Central Florida, USA • 6-volume set • ISBN 978-1-59904-949-6 Intelligent Information Technologies: Concepts, Methodologies, Tools, and Applications Vijayan Sugumaran, Oakland University, USA • 4-volume set • ISBN 978-1-59904-941-0 Information Security and Ethics: Concepts, Methodologies, Tools, and Applications Hamid Nemati, The University of North Carolina at Greensboro, USA • 6-volume set • ISBN 978-1-59904-937-3 Medical Informatics: Concepts, Methodologies, Tools, and Applications Joseph Tan, Wayne State University, USA • 4-volume set • ISBN 978-1-60566-050-9 Mobile Computing: Concepts, Methodologies, Tools, and Applications David Taniar, Monash University, Australia • 6-volume set • ISBN 978-1-60566-054-7 Multimedia Technologies: Concepts, Methodologies, Tools, and Applications Syed Mahbubur Rahman, Minnesota State University, Mankato, USA • 3-volume set • ISBN 978-1-60566-054-7 Virtual Technologies: Concepts, Methodologies, Tools, and Applications Jerzy Kisielnicki, Warsaw University, Poland • 3-volume set • ISBN 978-1-59904-955-7

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List of Contributors

Abowd, Gregory D. \ Georgia Institute of Technology, USA ............................................................ 370 Abuelma’atti, Omar \ Liverpool John Moores University, UK ........................................................ 171 Ahn, David \ Nyack College, USA ................................................................................................... 1358 Ahonen, Pasi \ VTT Technical Research Centre of Finland, Finland .............................................. 1425 Alahuhta, Petteri \ VTT Technical Research Centre of Finland, Finland ....................................... 1425 Andersson, Magnus \ Viktoria Institute, Sweden ............................................................................ 1079 Angelopoulos, Spyros P. \ Technical University of Crete, Greece .................................................. 1669 Aparajita, Upali \ Utkal University, India......................................................................................... 974 Apiletti, Daniele \ Politecnico di Torino, Italy .................................................................................. 853 Ayoade, John \ American University of Nigeria, Nigeria................................................................ 1374 Babulak, Eduard \ Fairleigh Dickinson University, Canada ......................................................... 1669 Bakhouya, M. \ The George Washington University, Washington DC, USA..................................... 182 Ballagas, Rafael \ RWTH Aachen University, Germany .................................................................... 439 Bang, Jounghae \ Penn State University Mont Alto, USA ................................................................. 941 Baralis, Elena \ Politecnico di Torino, Italy ...................................................................................... 853 Barricelli, Barbara R. \ Università degli Studi di Milano, Italy ....................................................... 212 Barros, Alistair \ SAP Research, Australia ...................................................................................... 1688 Bataille, Fabien \ Alcatel-Lucent Bell Labs, France ....................................................................... 1643 Berbegal, Nídia \ Universitat Pompeu Fabra, Spain......................................................................... 353 Berzunza, Gustavo \ CICESE, Mexico............................................................................................ 1786 Billinghurst, Mark \ Human Interface Technology Laboratory New Zealand– University of Canterbury, New Zealand .......................................................................................... 741 Borchers, Jan \ RWTH Aachen University, Germany........................................................................ 439 Boslau, Madlen \ Georg-August-Universität Göttingen, Germany ........................................... 44, 1098 Boye, Niels \ University of Aalborg, Denmark ................................................................................... 764 Briffault, Xavier \ CESAMES UMR 8136, Université René-Descartes Paris V, France .................. 389 Briggs, Pam \ Northumbria University, UK..................................................................................... 1408 Brook, Phillip W J \ University of Western Sydney, Australia ........................................................ 1039 Bruno, Giulia \ Politecnico di Torino, Italy ....................................................................................... 853 Butcher, T. \ University of Hull Logistics Institute (UHLI), UK ........................................................ 823 Buyurgan, Nebil \ University of Arkansas, USA ............................................................................... 867 Byrne, Caroline \ Institute of Technology Carlow, Ireland ............................................................... 129 Calafate, Carlos Tavares \ Technical University of Valencia, Spain ................................................ 503 Calleros, Juan Manuel González \ Université catholique de Louvain, Louvain School of Management (LSM), Belgium ............................................................................ 253

Camarata, Ken \ KDF Architecture, USA ......................................................................................... 730 Cano, Jose \ Technical University of Valencia, Spain ........................................................................ 503 Cano, Juan-Carlos \ Technical University of Valencia, Spain .......................................................... 503 Carvalho, João Álvaro \ University of Minho, Portugal .................................................................. 408 Cerquitelli, Tania \ Politecnico di Torino, Italy ................................................................................ 853 Chamberlain, Alan \ University of Nottingham, UK....................................................................... 1179 Chang, Elizabeth \ Curtin University of Technology, Australia .......................................................... 82 Chang, Flora Chia-I \ Tamkang University, China ........................................................................... 557 Chang, She-I \ National Chung Cheng University, Taiwan ............................................................. 1122 Chen, Yen-Jung \ National University of Tainan, Taiwan ................................................................. 520 Cheok, Adrian David \ National University of Singapore, Singapore .............................................. 905 Chiu, Yuh-Wen \ National Yunlin University of Science & Technology, Taiwan ............................ 1122 Choi, Inyoung \ Georgetown University, USA................................................................................... 941 Choi, Yongsoon \ National University of Singapore, Singapore........................................................ 905 Chong, Jimmy \ Nanyang Technological University, Singapore......................................................... 20 Chorianopoulos, Konstantinos \ Bauhaus University of Weimar, Germany .................................... 717 Chowdhury, Mohammad M. R. \ University Graduate Center – UniK, Norway ......................... 1067 Clarke, Dave \ GXS, USA .................................................................................................................. 581 Corchado, Juan M. \ Universidad de Salamanca, Spain .................................................................. 833 Coyle, Lorcan \ University College Dublin, Ireland ......................................................................... 145 Crellin, David \ Abingtom Partners, UK ......................................................................................... 1179 Cuozzo, Félix \ ENSICAEN, France .................................................................................................. 112 Dillon, Teresa \ Polar Produce, UK ................................................................................................. 1179 Do, Ellen Yi-Luen \ Georgia Institute of Technology, USA ............................................................... 730 Dorsch, Tillmann \ Tampere University of Technology, Finland .................................................... 1626 Duh, Henry B. L. \ Nanyang Technological University, Singapore .................................................... 20 Dwivedi, A. \ University of Hull, UK ................................................................................................. 823 Edegger, Francika \ evolaris Privatstiftung, Austria ...................................................................... 1156 Eikerling, Heinz-Josef \ Siemens AG SIS C-LAB, Germany ............................................................. 462 Eldin, Amr Ali \ Accenture BV, The Netherlands............................................................................. 1465 El-Nasr, Magy Seif \ Penn State University, USA ........................................................................... 1720 Elwood, Susan A. \ Texas A&M University, Corpus Christi, USA .................................................... 511 Etter, Stephanie \ Mount Aloysius College, USA ............................................................................ 1350 Favela, Jesus \ CICESE, Mexico...................................................................................................... 1786 Fergus, Paul \ Liverpool John Moores University, UK ..................................................................... 171 Fernandes, José Eduardo \ Bragança Polytechnic Institute, Portugal ............................................ 408 Fraser, Danaë Stanton \ University of Bath, UK ............................................................................ 1179 Friedewald, Michael \ Fraunhofer Institute Systems and Innovation Research, Germany ............ 1425 Gaber, J. \ Université de Technologie de Belfort-Montbéliard, France ............................................ 182 Galambosi, Agnes \ The University of North Carolina at Charlotte, USA...................................... 1250 García, Josefina Guerrero \ Université catholique de Louvain, Louvain School of Management (LSM), Belgium ............................................................................ 253 Garg, Miti \ The Logistics Institute – Asia Pacific, Singapore ........................................................ 1284 Gaunet, Florence \ Laboratoire Eco-Anthropologie et Ethnobiologie UMR 5145, CNRS, France .. 389 Germanakos, Panagiotis \ National & Kapodistrian University of Athens, Greece ........................ 309 Glambedakis, Antony \ University of Western Sydney, Australia ..................................................... 993

Glancy, Maxine \ BBC Research & Innovation, UK ....................................................................... 1179 Godara, Varuna \ University of Western Sydney, Australia .................................................... 234, 1199 Goh, Mark \ NUS Business School, The Logistics Institute – Asia Pacific, Singapore ................... 1284 Gomez, Laurent \ SAP Research, France ....................................................................................... 1481 Gosain, Sanjay \ The Capital Group Companies, USA ..................................................................... 581 Gower, Amanda \ BT Innovate, UK................................................................................................. 1179 Gower, Andrew \ BT Innovate, UK.................................................................................................. 1179 Gross, Mark D. \ Carnegie Mellon University, USA ......................................................................... 730 Gupta, Sumeet \ Shri Sankaracarya Institute of Management and Technology, India ................... 1284 Gurevych, Iryna \ Technische Universität Darmstadt, Germany ......................................................... 1 Gutiérrez, Jairo A. \ University of Auckland, New Zealand ................................................... 156, 1301 Hagenhoff, Svenja \ Georg-August-Universität Göttingen, Germany ................................................ 44 Hair, M. \ University of the West of Scotland, UK ........................................................................... 1315 Haller, Michael \ Upper Austria University of Applied Sciences–Digital Media, Austria ................ 741 Hallikas, Jukka \ Lappeenranta University of Technology, Finland............................................... 1052 Harboe, Gunnar \ Motorola, USA ..................................................................................................... 678 Hardgrave, Bill C. \ University of Arkansas, USA ............................................................................ 867 Hattori, Fumio \ Ritsumeikan University, Japan ............................................................................. 1762 Hayes, Gillian R. \ Georgia Institute of Technology, USA................................................................. 370 Hazlewood, William R. \ Indiana University Bloomington, USA ..................................................... 145 Huang, Elaine \ Motorola, USA ......................................................................................................... 678 Humanes, Pabo Roman \ Tampere University of Technology, Finland .......................................... 1626 Hung, Patrick C. K. \ University of Ontario Institute of Technology, Canada ............................... 1358 Hwang, Gwo-Jen \ National University of Tainan, Taiwan .............................................................. 520 Hwang, Jong-Sung \ National Information Society Agency, Korea ................................................ 1601 Iachello, Giovanni \ Georgia Institute of Technology, USA .............................................................. 370 Inakage, Masa \ Keio University, Japan............................................................................................ 206 Jentzsch, Ric \ Compucat Research Pty Limited, Australia .............................................................. 782 Johnson, Stephen \ Mobility Research Centre, UK ........................................................................... 707 Joly, Adrien \ Alcatel-Lucent Bell Labs, France Alcatel-Lucent Bell Labs, France & Universite deLyon, LIRIS/INSA, France ................................................................................... 1643 Jöst, Matthias \ European Media Laboratory GmbH, Germany..................................................... 1006 Kallenbach, Jan \ Helsinki University of Technology, Finland ......................................................... 717 Kameas, Achilles D. \ Hellenic Open University and Computer Technology Institute / DAISy group, Greece ....................................................................................................................... 330 Karaiskos, Dimitrios C. \ Athens University of Business and Economics, Greece ........................ 1106 Karmakar, Nemai Chandra \ Monash University, Australia ........................................................... 648 Karyda, Maria \ University of the Aegean, Greece ......................................................................... 1331 Kaspar, Christian \ Georg-August-Universität Göttingen, Germany ................................................. 44 Katsumoto, Yuichiro \ Keio University, Japan ................................................................................. 206 Kehoe, Dennis \ University of Liverpool, UK .................................................................................. 1228 Kientz, Julie A. \ Georgia Institute of Technology, USA ................................................................... 370 Kim, Tschangho John \ University of Illinois at Urbana-Champaign, USA .................................. 1613 Kinoshita, Tetsuo \ Tohoku University, Japan ................................................................................. 1762 Kitsios, Fotis C. \ Technical University of Crete, Greece ................................................................ 1669 Kittl, Christian \ evolaris Privatstiftung, Austria & Karl-Franzens University, Austria ................ 1156

Knuth, Peter \ Technical University of Košice, Slovakia ................................................................ 1293 Koh, Sze Ling \ Nanyang Technological University, Singapore.......................................................... 20 Koivumäki, Timo \ VTT Technical Research Centre of Finland, Finland ...................................... 1021 Koskela, Kaisa \ University of Oulu, Finland ................................................................................. 1021 Kourouthanassis, Panayiotis E. \ Athens University of Business and Economics, Greece............ 1106 Laube, Annett \ SAP Research, France ........................................................................................... 1481 LeDonne, Keith \ Robert Morris University, USA........................................................................... 1350 Lee, Cheon-Pyo \ Carson-Newman College, USA ............................................................................ 845 Lee, Deirdre \ Trinity College Dublin, Ireland .................................................................................. 488 Lee, Mark J. W. \ Charles Sturt University, Australia ...................................................................... 524 Lekkas, Zacharias \ National & Kapodistrian University of Athens, Greece................................... 309 Leu, Huei \ Industrial Technology Research Institute, Taiwan ........................................................ 1219 Li, Dong \ University of Liverpool, UK............................................................................................ 1228 Li, Grace \ University of Technology, Sydney, Australia ................................................................. 1450 Li, Haifei \ Union University, USA .................................................................................................. 1358 Lietke, Britta \ Georg-August-Universität Göttingen, Germany............................................... 44, 1098 Lin, Chad \ Edith Cowan University, Australia ............................................................................... 1219 Lin, Koong \ Tainan National University of the Arts, Taiwan ......................................................... 1219 Lindgren, Rikard \ University of Gothenburg, Sweden & Viktoria Institute, Sweden .................... 1079 Little, Linda \ Northumbria University, UK .................................................................................... 1408 Littman, Marlyn Kemper \ Nova Southeastern University, USA .................................................... 815 Liu, Kinchung \ University of Liverpool, UK.................................................................................. 1228 Liu, Wei \ National University of Singapore, Singapore ................................................................... 905 Lo, Janice \ Baylor University, USA .................................................................................................. 867 Lugmayr, Artur \ Tampere University of Technology, Finland ............................................... 717, 1626 Lyardet, Fernando \ Technische Universität Darmstadt, Germany................................................ 1562 Machado, Ricardo J. \ University of Minho, Portugal ..................................................................... 408 Mangaraj, B.K. \ XLRI Jamshepur, School of Business and Human Resources, Jamshedpur, India ............................................................................................................................ 974 Manzoni, Pietro \ Technical University of Valencia, Spain ............................................................... 503 Marcante, Andrea \ Università degli Studi di Milano, Italy ............................................................. 212 Maret, Pierre \ Université de Lyon, France .................................................................................... 1643 Martin, Patrick \ Queen’s University, Canada.................................................................................. 276 Massey, Noel \ Motorola, USA ........................................................................................................... 678 Mazzoleni, Pietro \ IBM Watson Research, USA ............................................................................... 462 Meier, René \ Trinity College Dublin, Ireland ................................................................................... 488 Mei-Ling, Charissa Lim \ Nanyang Technological University, Singapore....................................... 905 Melski, Adam \ Georg-August-Universität Göttingen, Germany ........................................................ 44 Memmola, Massimo \ Catholic University, Italy .............................................................................. 623 Merabti, Madjid \ Liverpool John Moores University, UK .............................................................. 171 Metcalf, Crysta \ Motorola, USA ...................................................................................................... 678 Mikkonen, Karri \ TeliaSonera, Sweden ......................................................................................... 1052 Minakshi, \ CCS Haryana Agricultural University, India ................................................................ 957 Mitrou, Lilian \ University of the Aegean, Greece .......................................................................... 1331 Modrák, Vladimír \ Technical University of Košice, Slovakia ....................................................... 1293 Mohammadian, Masoud \ University of Canberra, Australia ......................................................... 782

Molinero, Ashli M. \ Robert Morris University, USA...................................................................... 1350 Mourlas, Constantinos \ National & Kapodistrian University of Athens, Greece ........................... 309 Mühlhäuser, Max \ Technische Universität Darmstadt, Germany................................................ 1, 717 Mulder, Ingrid \ Telematica Instituut and Rotterdam University, The Netherlands.......................... 191 Mussio, Piero \ Università degli Studi di Milano, Italy ..................................................................... 212 Nabelsi, Véronique \ École Polytechnique de Montréal, Canada................................................... 1144 Natkin, Stéphane \ Conservatoire National des Arts et Métiers, Pans, France.............................. 1738 Navarro-Prieto, Raquel \ Fundació Barcelona Media, Spain .......................................................... 353 Nestor, Susan J. \ Robert Morris University, USA .......................................................................... 1350 Nguyen, Ta Huynh Duy \ National University of Singapore, Singapore .......................................... 905 Niemelä, Marketta \ VTT Technical Research Centre of Finland, Finland .................................... 1396 Noll, Josef \ University Graduate Center – UniK, Norway ............................................................. 1067 Novak, Ashley \ Motorola, USA ......................................................................................................... 678 O’Grady, Michael \ University College Dublin, Ireland .................................................................. 129 O’Hare, Gregory \ University College Dublin, Ireland .................................................................... 129 Oh, Yeonjoo \ Carnegie Mellon University, USA .............................................................................. 730 Özelkan, Ertunga C. \ The University of North Carolina at Charlotte, USA ................................. 1250 Padula, Marco \ Istituto per le Tecnologie della Costruzione – Consiglio Nazionale delle Ricerche, Italy........................................................................................... 212 Palo, Teea \ University of Oulu, Finland.......................................................................................... 1021 Palumbo, Giovanna \ Ospedale Valduce, Italy ................................................................................. 623 Papatheodorou, Christos \ Ionian University, Greece...................................................................... 931 Park, Kevin \ University of Auckland, New Zealand ......................................................................... 156 Parry, David \ Auckland University of Technology, New Zealand .................................................... 802 Pasquet, Marc \ GREYC Laboratory (ENSICAEN – Université Caen Basse Normandie - CNRS), France .............................................................................................................................. 112 Patel, Shwetak N. \ Georgia Institute of Technology, USA ............................................................... 370 Peiris, Roshan \ National University of Singapore, Singapore ......................................................... 905 Petrovic, Otto \ evolaris Privatstiftung, Austria & Karl-Franzens University, Austria .................. 1156 Phillips, Patricia G. \ Duquesne University, USA ........................................................................... 1350 Pitkänen, Olli \ Helsinki Institute for Information Technology (HIIT), Finland ............................. 1396 Pohl, Alexandra \ Berlin-Brandenburg (rbb) Innovationsprojekte, Germany .................................. 717 Potdar, Vidyasagar \ Curtin University of Technology, Australia....................................................... 82 Powley, Wendy \ Queen’s University, Canada................................................................................... 276 Prasad, Gaya \ CCS Haryana Agricultural University, India ........................................................... 957 Provenza, Loredana Parasiliti \ Università degli Studi di Milano, Italy ......................................... 212 Pynnönen, Mikko \ Lappeenranta University of Technology, Finland ........................................... 1052 Qui, Tran Cong Thien \ National University of Singapore, Singapore ............................................ 905 Raibulet, Claudia \ Universitá degli Studi di Milano-Bicocca, Italy .............................................. 1527 Ramos, Carlos \ Polytechnic of Porto, Portugal ............................................................................... 137 Ramsay, J. \ University of the West of Scotland, UK ....................................................................... 1315 Rantakokko, Tapani \ Finwe LTD, Finland.................................................................................... 1425 Renaud, K. V. \ University of Glasgow, UK .................................................................................... 1315 Reynaud, Joan \ GREYC Laboratory (ENSICAEN – Université Caen Basse Normandie - CNRS), France .............................................................................................................................. 112 Rohs, Michael \ Deutsche Telekom Laboratories, Germany ............................................................. 439

Roibás, Anxo Cereijo \ SCMIS, University of Brighton, UK .................................................. 707, 1498 Romano, Guy \ Motorola, USA ......................................................................................................... 678 Rossini, Mauro \ Ospedale Valduce, Italy ......................................................................................... 623 Rouillard, José \ Laboratoire LIFL - Université de Lille 1, France................................................ 1582 Roussos, George \ University of London, UK.................................................................................. 1517 Sadri, Fariba \ Imperial College London, UK................................................................................... 121 Samaras, George \ University of Cyprus, Cyprus ............................................................................. 309 Savolainen, Petri \ Lappeenranta University of Technology, Finland ............................................ 1052 Scala, Paolo L. \ Istituto per le Tecnologie della Costruzione – Consiglio Nazionale delle Ricerchev, Italy ...................................................................................... 212 Seah, Lily Leng-Hiang \ Nanyang Technological University, Singapore ........................................... 20 Sedlar, Patricia \ Johannes Kepler University, Austria ....................................................................... 35 See, Stanley \ Nanyang Technological University, Singapore ............................................................. 20 Segura, Daniela \ CICESE, Mexico ................................................................................................. 1786 Sheridan, Jennifer G. \ BigDog Interactive Ltd., UK ....................................................................... 439 Shih, Dong-Her \ National Yunlin University of Science & Technology, Taiwan............................ 1122 Shim, J. P. \ Mississippi State University, USA .................................................................................. 845 Shiratori, Norio \ Tohoku University, Japan ................................................................................... 1762 Soon, Chin-Boo \ The University of Auckland, New Zealand ................................................... 65, 1301 Sorniotti, Alessandro \ SAP Research, France ............................................................................... 1481 Stathis, Kostas \ Royal Holloway, University of London, UK ........................................................... 121 Stefanescu, Florina \ ePoly Centre of Expertise in Electronic Commerce, Canada ....................... 1144 Stojanovic, Zoran \ IBM Nederland BV, The Netherlands .............................................................. 1465 Suganuma, Takuo \ Tohoku University, Japan ................................................................................ 1762 Sugawara, Kenji \ Chiba Institute of Technology, Japan ................................................................ 1762 Symonds, Judith A. \ Auckland University of Technology, New Zealand ............................... 802, 1374 Tähtinen, Jaana \ University of Oulu, Finland ............................................................................... 1021 Tapia, Dante I. \ Universidad de Salamanca, Spain.......................................................................... 833 Tatnall, Arthur \ Victoria University, Australia .................................................................................. 28 Teh, Keng Soon \ National University of Singapore, Singapore ....................................................... 905 Tentori, Mónica \ CICESE and Universidad Autónoma de Baja California, Mexico..................... 1786 Terrenghi, Lucia \ Vodafone Group R&D, Germany ........................................................................ 191 Theng, Yin-Leng \ Nanyang Technological University, Singapore ............................................. 20, 905 Thillairajah, Velan \ EAI Technologies, USA .................................................................................... 581 Tokuhisa, Satoru \ Keio University, Japan ....................................................................................... 206 Trček, Denis \ University of Ljubljana, Slovenia ............................................................................. 1386 Truong, Khai N. \ University of Toronto, Canada ............................................................................. 370 Tsakonas, Giannis \ Ionian University, Greece ................................................................................. 931 Tsianos, Nikos \ National & Kapodistrian University of Athens, Greece .......................................... 309 Tullio, Joe \ Motorola, USA ............................................................................................................... 678 Ueki, Atsuro \ Keio University, Japan ............................................................................................... 206 Vacquez, Delphine \ ENSICAEN, France.......................................................................................... 112 van ‘t Hooft, Mark \ Kent State University, USA .............................................................................. 886 Vanderdonckt, Jean \ Université catholique de Louvain, Louvain School of Management (LSM), Belgium ............................................................................ 253 Vasilakos, Athanasios V. \ University of Peloponnese, Greece ............................................... 905, 1720

Veronikis, Spyros \ Ionian University, Greece .................................................................................. 931 Vildjiounaite, Elena \ VTT Technical Research Centre of Finland, Finland .................................. 1425 Vowels, Susan A. \ Washington College, USA ..................................................................................... 54 Walker, Ronald T. \ University of Arkansas, USA ............................................................................ 867 Wang, Te-Hua \ Tamkang University, China ..................................................................................... 557 Wang, Xiaojun \ University of Liverpool, UK ................................................................................. 1228 Watson, Genevieve \ University of Western Sydney, Australia.......................................................... 993 Weller, Michael Philetus \ Carnegie Mellon University, USA .......................................................... 730 Wilson, Kirk \ CA Inc., Canada ........................................................................................................ 276 Woodgate, Dawn \ University of Bath, UK ..................................................................................... 1179 Wright, David \ Trilateral Research and Consulting, UK............................................................... 1425 Wu, Chen \ Curtin University of Technology, Australia ...................................................................... 82 Wu, Ting-Ting \ National University of Tainan, Taiwan ................................................................... 520 Wyld, David C. \ Southeastern Louisiana University, USA .............................................................. 594 Xu, Heng \ The Pennsylvania State University, USA ....................................................................... 1284 Yan, Chen \ Conservatoire National des Arts et Métiers, Pans, France ......................................... 1738 Yan, Lu \ University College London, UK ....................................................................................... 1549 Yen, David C. \ Miami University, USA........................................................................................... 1122 Zebedee, Jared \ Queen’s University, Canada................................................................................... 276 Zhang, Jia \ Northern Illinois University, USA ............................................................................... 1358 Zoumboulakis, Michael \ University of London, UK ..................................................................... 1517

Contents

Volume I Section I. Fundamental Concepts and Theories This section serves as the foundation for this exhaustive reference source by addressing crucial theories essential to the understanding of ubiquitous and pervasive computing. Chapters found within this section provide a framework in which to position ubiquitous and pervasive tools and technologies within the field of information science and technology. Individual contributions provide overviews of ubiquitous grids, ambient intelligence, ubiquitous networking, and radio frequency identification (RFID). Within this introductory section, the reader can learn and choose from a compendium of expert research on the elemental theories underscoring the research and application of ubiquitous and pervasive computing. Chapter 1.1. Introduction to Ubiquitous Computing............................................................................... 1 Max Mühlhäuser, Technische Universität Darmstadt, Germany Iryna Gurevych, Technische Universität Darmstadt, Germany Chapter 1.2. Ubiquitous Computing History, Development, and Scenarios......................................... 20 Jimmy Chong, Nanyang Technological University, Singapore Stanley See, Nanyang Technological University, Singapore Lily Leng-Hiang Seah, Nanyang Technological University, Singapore Sze Ling Koh, Nanyang Technological University, Singapore Yin-Leng Theng, Nanyang Technological University, Singapore Henry B. L. Duh, Nanyang Technological University, Singapore Chapter 1.3. The Ubiquitous Portal....................................................................................................... 28 Arthur Tatnall, Victoria University, Australia Chapter 1.4. The Ubiquitous Grid.......................................................................................................... 35 Patricia Sedlar, Johannes Kepler University, Austria

Chapter 1.5. RFID Technologies and Applications................................................................................ 44 Christian Kaspar, Georg-August-Universität Göttingen, Germany Adam Melski, Georg-August-Universität Göttingen, Germany Britta Lietke, Georg-August-Universität Göttingen, Germany Madlen Boslau, Georg-August-Universität Göttingen, Germany Svenja Hagenhoff, Georg-August-Universität Göttingen, Germany Chapter 1.6. Understanding RFID (Radio Frequency Identification).................................................... 54 Susan A. Vowels, Washington College, USA Chapter 1.7. Radio Frequency Identification History and Development............................................... 65 Chin-Boo Soon, The University of Auckland, New Zealand Chapter 1.8. Automated Data Capture Technologies: RFID.................................................................. 82 Vidyasagar Potdar, Curtin University of Technology, Australia Chen Wu, Curtin University of Technology, Australia Elizabeth Chang, Curtin University of Technology, Australia Chapter 1.9. Contactless Payment with RFID and NFC...................................................................... 112 Marc Pasquet, GREYC Laboratory (ENSICAEN – Université Caen Basse Normandie CNRS), France Delphine Vacquez, ENSICAEN, France Joan Reynaud, GREYC Laboratory (ENSICAEN – Université Caen Basse Normandie CNRS), France Félix Cuozzo, ENSICAEN, France Chapter 1.10. Ambient Intelligence..................................................................................................... 121 Fariba Sadri, Imperial College London, UK Kostas Stathis, Royal Holloway, University of London, UK Chapter 1.11. Ambient Intelligence in Perspective.............................................................................. 129 Caroline Byrne, Institute of Technology Carlow, Ireland Michael O’Grady, University College Dublin, Ireland Gregory O’Hare, University College Dublin, Ireland Chapter 1.12. Ambient Intelligence Environments.............................................................................. 137 Carlos Ramos, Polytechnic of Porto, Portugal Chapter 1.13. On Ambient Information Systems: Challenges of Design and Evaluation................... 145 William R. Hazlewood, Indiana University Bloomington, USA Lorcan Coyle, University College Dublin, Ireland Chapter 1.14. Basics of Ubiquitous Networking................................................................................. 156 Kevin Park, University of Auckland, New Zealand Jairo A. Gutiérrez, University of Auckland, New Zealand

Chapter 1.15. Networked Appliances and Home Networking: Internetworking the Home................ 171 Madjid Merabti, Liverpool John Moores University, UK Paul Fergus, Liverpool John Moores University, UK Omar Abuelma’atti, Liverpool John Moores University, UK Section II. Development and Design Methodologies This section provides in-depth coverage of conceptual architectures, frameworks and methodologies related to the design of ubiquitous and pervasive tools, models, and interfaces. Throughout these contributions, fundamental development methodologies are presented and discussed. From broad examinations to specific discussions of particular frameworks and infrastructures, the research found within this section spans the discipline while also offering detailed, specific discussions. Basic designs, as well as abstract developments, are explained within these chapters, and frameworks for designing successful interactive systems, educational models, and mobile devices are examined. Chapter 2.1. Ubiquitous and Pervasive Application Design................................................................ 182 M. Bakhouya, The George Washington University, Washington DC, USA J. Gaber, Université de Technologie de Belfort-Montbéliard, France Chapter 2.2. When Ubiquitous Computing Meets Experience Design: Identifying Challenges for Design and Evaluation................................................................................................. 191 Ingrid Mulder, Telematica Instituut and Rotterdam University, The Netherlands Lucia Terrenghi, Vodafone Group R&D, Germany Chapter 2.3. Designing Ubiquitous Content for Daily Lifestyle......................................................... 206 Masa Inakage, Keio University, Japan Atsuro Ueki, Keio University, Japan Satoru Tokuhisa, Keio University, Japan Yuichiro Katsumoto, Keio University, Japan Chapter 2.4. Designing Pervasive and Multimodal Interactive Systems: An Approach Built on the Field................................................................................................................................. 212 Barbara R. Barricelli, Università degli Studi di Milano, Italy Piero Mussio, Università degli Studi di Milano, Italy Marco Padula, Istituto per le Tecnologie della Costruzione – Consiglio Nazionale delle Ricerche, Italy Andrea Marcante, Università degli Studi di Milano, Italy Loredana Parasiliti Provenza, Università degli Studi di Milano, Italy Paolo L. Scala, Istituto per le Tecnologie della Costruzione – Consiglio Nazionale delle Ricerchev, Italy Chapter 2.5. Pervasive Computing: A Conceptual Framework........................................................... 234 Varuna Godara, University of Western Sydney, Australia

Chapter 2.6. Developing User Interfaces for Community-Oriented Workflow Information Systems............................................................................................................................ 253 Josefina Guerrero García, Université catholique de Louvain, Louvain School of Management (LSM), Belgium Jean Vanderdonckt, Université catholique de Louvain, Louvain School of Management (LSM), Belgium Juan Manuel González Calleros, Université catholique de Louvain, Louvain School of Management (LSM), Belgium Chapter 2.7. An Adaptable Context Management Framework for Pervasive Computing................... 276 Jared Zebedee, Queen’s University, Canada Patrick Martin, Queen’s University, Canada Kirk Wilson, CA Inc., Canada Wendy Powley, Queen’s University, Canada Chapter 2.8. Incorporating Human Factors in the Development of Context-Aware Personalized Applications: The Next Generation of Intelligent User Interfaces................................. 309 Nikos Tsianos, National & Kapodistrian University of Athens, Greece Panagiotis Germanakos, National & Kapodistrian University of Athens, Greece Zacharias Lekkas, National & Kapodistrian University of Athens, Greece Constantinos Mourlas, National & Kapodistrian University of Athens, Greece George Samaras, University of Cyprus, Cyprus Chapter 2.9. Deploying Ubiquitous Computing Applications on Heterogeneous Next Generation Networks.................................................................................................................. 330 Achilles D. Kameas, Hellenic Open University and Computer Technology Institute / DAISy group, Greece Chapter 2.10. Convergence Broadcast and Telecommunication Services: What are Real Users’ Needs?............................................................................................................... 353 Raquel Navarro-Prieto, Fundació Barcelona Media, Spain Nídia Berbegal, Universitat Pompeu Fabra, Spain Chapter 2.11. Designing a Ubiquitous Audio-Based Memory Aid...................................................... 370 Shwetak N. Patel, Georgia Institute of Technology, USA Khai N. Truong, University of Toronto, Canada Gillian R. Hayes, Georgia Institute of Technology, USA Giovanni Iachello, Georgia Institute of Technology, USA Julie A. Kientz, Georgia Institute of Technology, USA Gregory D. Abowd, Georgia Institute of Technology, USA Chapter 2.12. A Navigational Aid for Blind Pedestrians Designed with Userand Activity-Centered Approaches...................................................................................................... 389 Florence Gaunet, Laboratoire Eco-Anthropologie et Ethnobiologie UMR 5145, CNRS, France Xavier Briffault, CESAMES UMR 8136, Université René-Descartes Paris V, France

Chapter 2.13. Model-Driven Development for Pervasive Information Systems................................. 408 José Eduardo Fernandes, Bragança Polytechnic Institute, Portugal Ricardo J. Machado, University of Minho, Portugal João Álvaro Carvalho, University of Minho, Portugal Chapter 2.14. The Design Space of Ubiquitous Mobile Input............................................................. 439 Rafael Ballagas, RWTH Aachen University, Germany Michael Rohs, Deutsche Telekom Laboratories, Germany Jennifer G. Sheridan, BigDog Interactive Ltd., UK Jan Borchers, RWTH Aachen University, Germany Chapter 2.15. A Methodology for the Design, Development and Validation of Adaptive and Context-Aware Mobile Services................................................................................................... 462 Heinz-Josef Eikerling, Siemens AG SIS C-LAB, Germany Pietro Mazzoleni, IBM Watson Research, USA Chapter 2.16. Context-Aware Services for Ambient Environments.................................................... 488 René Meier, Trinity College Dublin, Ireland Deirdre Lee, Trinity College Dublin, Ireland Section III. Tools and Technologies This section presents extensive coverage of the tools and specific technologies that change the way we interact with and respond to our environments. These chapters provide an in-depth analysis of the use and development of innumerable devices and tools, while also providing insight into new and upcoming technologies, theories, and instruments that will soon be commonplace. Within these rigorously researched chapters, readers are presented with examples of specific tools, such as video surveillance systems, smart antennas, mobile technologies, and GIS systems. In addition, the successful implementation and resulting impact of these various tools and technologies are discussed within this collection of chapters. Chapter 3.1. Deploying Pervasive Technologies................................................................................. 503 Juan-Carlos Cano, Technical University of Valencia, Spain Carlos Tavares Calafate, Technical University of Valencia, Spain Jose Cano, Technical University of Valencia, Spain Pietro Manzoni, Technical University of Valencia, Spain Chapter 3.2. Embedding Ubiquitous Technologies............................................................................. 511 Susan A. Elwood, Texas A&M University, Corpus Christi, USA Chapter 3.3. Ubiquitous Computing Technologies in Education......................................................... 520 Gwo-Jen Hwang, National University of Tainan, Taiwan Ting-Ting Wu, National University of Tainan, Taiwan Yen-Jung Chen, National University of Tainan, Taiwan

Chapter 3.4. Mobile and Pervasive Technology in Education and Training: Potential and Possibilities, Problems and Pitfalls............................................................................................... 524 Mark J. W. Lee, Charles Sturt University, Australia Chapter 3.5. A SCORM Compliant Courseware Authoring Tool for Supporting Pervasive Learning............................................................................................................................... 557 Te-Hua Wang, Tamkang University, China Flora Chia-I Chang, Tamkang University, China

Volume II Chapter 3.6. Realizing the Promise of RFID: Insights from Early Adopters and the Future Potential....................................................................................................................... 581 Velan Thillairajah, EAI Technologies, USA Sanjay Gosain, The Capital Group Companies, USA Dave Clarke, GXS, USA Chapter 3.7. The Little Chip that Could: The Public Sector and RFID............................................... 594 David C. Wyld, Southeastern Louisiana University, USA Chapter 3.8. Web & RFId Technology: New Frontiers in Costing and Process Management for Rehabilitation Medicine........................................................................................... 623 Massimo Memmola, Catholic University, Italy Giovanna Palumbo, Ospedale Valduce, Italy Mauro Rossini, Ospedale Valduce, Italy Chapter 3.9. Smart Antennas for Automatic Radio Frequency Identification Readers....................... 648 Nemai Chandra Karmakar, Monash University, Australia Chapter 3.10. Getting to Know Social Television: One Team’s Discoveries from Library to Living Room.............................................................................................................. 678 Gunnar Harboe, Motorola, USA Elaine Huang, Motorola, USA Noel Massey, Motorola, USA Crysta Metcalf, Motorola, USA Ashley Novak, Motorola, USA Guy Romano, Motorola, USA Joe Tullio, Motorola, USA Chapter 3.11. Pervasive iTV and Creative Networked Multimedia Systems...................................... 707 Anxo Cereijo Roibás, SCMIS, University of Brighton, UK Stephen Johnson, Mobility Research Centre, UK

Chapter 3.12. Ambient Media and Home Entertainment..................................................................... 717 Artur Lugmayr, Tampere University of Technology, Finland Alexandra Pohl, Berlin-Brandenburg (rbb) Innovationsprojekte, Germany Max Müehhäueser, Technische Universitat Darmstädt, Germany Jan Kallenbach, Helsinki University of Technology, Finland Konstantinos Chorianopoulos, Bauhaus University of Weimar, Germany Chapter 3.13. TeleTables and Window Seat: Bilocative Furniture Interfaces..................................... 730 Yeonjoo Oh, Carnegie Mellon University, USA Ken Camarata, KDF Architecture, USA Michael Philetus Weller, Carnegie Mellon University, USA Mark D. Gross, Carnegie Mellon University, USA Ellen Yi-Luen Do, Georgia Institute of Technology, USA Chapter 3.14. Interactive Tables: Requirements, Design Recommendations, and Implementation............................................................................................................................. 741 Michael Haller, Upper Austria University of Applied Sciences–Digital Media, Austria Mark Billinghurst, Human Interface Technology Laboratory New Zealand–University of Canterbury, New Zealand Section IV. Utilization and Application This section introduces and discusses the utilization and application of ubiquitous and pervasive computing technologies. These particular selections highlight, among other topics, pervasive healthcare, the utilization of handheld computers, and m-commerce. Contributions included in this section provide coverage of the ways in which technology increasingly becomes part of our daily lives through the seamless integration of specific tools into existing processes. Chapter 4.1. Pervasive Healthcare: Problems and Potentials.............................................................. 764 Niels Boye, University of Aalborg, Denmark Chapter 4.2. Intelligent Agent Framework for Secure Patient-Doctor Profiling and Profile Matching............................................................................................................................ 782 Masoud Mohammadian, University of Canberra, Australia Ric Jentzsch, Compucat Research Pty Limited, Australia Chapter 4.3. Using RFID to Track and Trace High Value Products: The Case of City Healthcare................................................................................................................................ 802 Judith A. Symonds, Auckland University of Technology, New Zealand David Parry, Auckland University of Technology, New Zealand Chapter 4.4. Implementing RFID Technology in Hospital Environments.......................................... 815 Marlyn Kemper Littman, Nova Southeastern University, USA

Chapter 4.5. RFID as the Critical Factor for Superior Healthcare Delivery........................................ 823 A. Dwivedi, University of Hull, UK T. Butcher, University of Hull Logistics Institute (UHLI), UK Chapter 4.6. An Ambient Intelligence Based Multi-Agent System for Alzheimer Health Care......... 833 Dante I. Tapia, Universidad de Salamanca, Spain Juan M. Corchado, Universidad de Salamanca, Spain Chapter 4.7. Ubiquitous Healthcare: Radio Frequency Identification (RFID) in Hospitals................ 845 Cheon-Pyo Lee, Carson-Newman College, USA J. P. Shim, Mississippi State University, USA Chapter 4.8. Ubiquitous Risk Analysis of Physiological Data............................................................ 853 Daniele Apiletti, Politecnico di Torino, Italy Elena Baralis, Politecnico di Torino, Italy Giulia Bruno, Politecnico di Torino, Italy Tania Cerquitelli, Politecnico di Torino, Italy Chapter 4.9. RFID in Healthcare: A Framework of Uses and Opportunities...................................... 867 Nebil Buyurgan, University of Arkansas, USA Bill C. Hardgrave, University of Arkansas, USA Janice Lo, Baylor University, USA Ronald T. Walker, University of Arkansas, USA Chapter 4.10. Tapping into Digital Literacy: Handheld Computers in the K-12 Classroom............... 886 Mark van ‘t Hooft, Kent State University, USA Chapter 4.11. Internet-Enabled User Interfaces for Distance Learning............................................... 905 Wei Liu, National University of Singapore, Singapore Keng Soon Teh, National University of Singapore, Singapore Roshan Peiris, National University of Singapore, Singapore Yongsoon Choi, National University of Singapore, Singapore Adrian David Cheok, National University of Singapore, Singapore Charissa Lim Mei-Ling, Nanyang Technological University, Singapore Yin-Leng Theng, Nanyang Technological University, Singapore Ta Huynh Duy Nguyen, National University of Singapore, Singapore Tran Cong Thien Qui, National University of Singapore, Singapore Athanasios V. Vasilakos, University of Peloponnese, Greece Chapter 4.12. Handhelds for Digital Libraries..................................................................................... 931 Spyros Veronikis, Ionian University, Greece Giannis Tsakonas, Ionian University, Greece Christos Papatheodorou, Ionian University, Greece

Chapter 4.13. South Korea: Vision of a Ubiquitous Network World................................................... 941 Jounghae Bang, Penn State University Mont Alto, USA Inyoung Choi, Georgetown University, USA Chapter 4.14. Ubiquitous Computing for Microbial Forensics and Bioterrorism............................... 957 Gaya Prasad, CCS Haryana Agricultural University, India Minakshi, CCS Haryana Agricultural University, India Section V. Organizational and Social Implications This section includes a wide range of research pertaining to the social and organizational impact of ubiquitous and pervasive computing around the world. Chapters included in this section analyze the cultural dimension of pervasive computing, consumer reactions to RFID, and user acceptance of technology. The inquiries and methods presented in this section offer insight into the implications of ubiquitous and pervasive computing at both an individual and organizational level, while also emphasizing potential areas of study within the discipline. Chapter 5.1. Cultural Dimension in the Future of Pervasive Computing............................................ 974 B.K. Mangaraj, XLRI Jamshepur, School of Business and Human Resources, Jamshedpur, India Upali Aparajita, Utkal University, India Chapter 5.2. Outline of the Human Factor Elements Evident with Pervasive Computers.................. 993 Genevieve Watson, University of Western Sydney, Australia Antony Glambedakis, University of Western Sydney, Australia Chapter 5.3. Adapting to the User...................................................................................................... 1006 Matthias Jöst, European Media Laboratory GmbH, Germany Chapter 5.4. How Research can Help to Create Commercially Successful Ubiquitous Services........................................................................................................................... 1021 Teea Palo, University of Oulu, Finland Kaisa Koskela, University of Oulu, Finland Timo Koivumäki, VTT Technical Research Centre of Finland, Finland Jaana Tähtinen, University of Oulu, Finland Chapter 5.5. Knowledge Sharing and Pervasive Computing: The Need for Trust and a Sense of History....................................................................................................................... 1039 Phillip W J Brook, University of Western Sydney, Australia Chapter 5.6. Ubiquitous Communication: Where is the Value Created in the Multi-Play Value Network?......................................................................................................... 1052 Mikko Pynnönen, Lappeenranta University of Technology, Finland Jukka Hallikas, Lappeenranta University of Technology, Finland Petri Savolainen, Lappeenranta University of Technology, Finland Karri Mikkonen, TeliaSonera, Sweden

Chapter 5.7. Identity Management for Wireless Service Access....................................................... 1067 Mohammad M. R. Chowdhury, University Graduate Center – UniK, Norway Josef Noll, University Graduate Center – UniK, Norway Chapter 5.8. Inscribing Interpretive Flexibility of Context Data in Ubiquitous Computing Environments: An Action Research Study of Vertical Standard Development..................................................................................................... 1079 Magnus Andersson, Viktoria Institute, Sweden Rikard Lindgren, University of Gothenburg, Sweden & Viktoria Institute, Sweden Chapter 5.9. Consumer Attitudes toward RFID Usage...................................................................... 1098 Madlen Boslau, Georg-August-Universität Göttingen, Germany Britta Lietke, Georg-August-Universität Göttingen, Germany Chapter 5.10. Determinants of User Acceptance for RFID Ticketing Systems................................. 1106 Dimitrios C. Karaiskos, Athens University of Business and Economics, Greece Panayiotis E. Kourouthanassis, Athens University of Business and Economics, Greece Chapter 5.11. An Empirical Study of Factors Affecting RFID’s Adoption in Taiwan....................... 1122 Dong-Her Shih, National Yunlin University of Science & Technology, Taiwan Yuh-Wen Chiu, National Yunlin University of Science & Technology, Taiwan She-I Chang, National Chung Cheng University, Taiwan David C. Yen, Miami University, USA Chapter 5.12. Impact of RFID Technology on Health Care Organizations....................................... 1144 Véronique Nabelsi, École Polytechnique de Montréal, Canada Florina Stefanescu, ePoly Centre of Expertise in Electronic Commerce, Canada Chapter 5.13. Learning by Pervasive Gaming: An Empirical Study................................................. 1156 Christian Kittl, evolaris Privatstiftung, Austria & Karl-Franzens University, Austria Francika Edegger, evolaris Privatstiftung, Austria Otto Petrovic, evolaris Privatstiftung, Austria & Karl-Franzens University, Austria Chapter 5.14. Using Mobile and Pervasive Technologies to Engage Formal and Informal Learners in Scientific Debate....................................................................................... 1179 Dawn Woodgate, University of Bath, UK Danaë Stanton Fraser, University of Bath, UK Amanda Gower, BT Innovate, UK Maxine Glancy, BBC Research & Innovation, UK Andrew Gower, BT Innovate, UK Alan Chamberlain, University of Nottingham, UK Teresa Dillon, Polar Produce, UK David Crellin, Abington Partners, UK

Volume III Section VI. Managerial Impact This section presents contemporary coverage of the managerial implications of ubiquitous and pervasive computing. Particular contributions address pervasive business infrastructure, RFID and the supply chain, and employee surveillance. The managerial research provided in this section allows executives, practitioners, and researchers to gain a better sense of how ubiquitous and pervasive computing can impact and inform practices and behavior. Chapter 6.1. Pervasive Business Infrastructure: The Network Technologies, Routing and Security Issues............................................................................................................................. 1199 Varuna Godara, University of Western Sydney, Australia Chapter 6.2. Decision Analysis for Business to Adopt RFID............................................................ 1219 Koong Lin, Tainan National University of the Arts, Taiwan Chad Lin, Edith Cowan University, Australia Huei Leu, Industrial Technology Research Institute, Taiwan Chapter 6.3. Intelligent Supply Chain Management with Automatic Identification Technology.................................................................................................................. 1228 Dong Li, University of Liverpool, UK Xiaojun Wang, University of Liverpool, UK Kinchung Liu, University of Liverpool, UK Dennis Kehoe, University of Liverpool, UK Chapter 6.4. When Does RFID Make Business Sense for Managing Supply Chain?....................... 1250 Ertunga C. Özelkan, The University of North Carolina at Charlotte, USA Agnes Galambosi, The University of North Carolina at Charlotte, USA Chapter 6.5. RFID and Supply Chain Visibility................................................................................ 1284 Sumeet Gupta, Shri Sankaracarya Institute of Management and Technology, India Miti Garg, The Logistics Institute – Asia Pacific, Singapore Heng Xu, The Pennsylvania State University, USA Mark Goh, NUS Business School, The Logistics Institute – Asia Pacific, Singapore Chapter 6.6. Security and Reliability of RFID Technology in Supply Chain Management............................................................................................................................ 1293 Vladimír Modrák, Technical University of Košice, Slovakia Peter Knuth, Technical University of Košice, Slovakia Chapter 6.7. Recognizing RFID as a Disruptive Technology............................................................ 1301 Chin-Boo Soon, The University of Auckland, New Zealand Jairo A. Gutiérrez, The University of Auckland, New Zealand

Chapter 6.8. Ubiquitous Connectivity & Work-Related Stress......................................................... 1315 J. Ramsay, University of the West of Scotland, UK M. Hair, University of the West of Scotland, UK K. V. Renaud, University of Glasgow, UK Chapter 6.9. Bridging the Gap between Employee Surveillance and Privacy Protection................. 1331 Lilian Mitrou, University of the Aegean, Greece Maria Karyda, University of the Aegean, Greece Section VII. Critical Issues This section addresses conceptual and theoretical issues related to the field of ubiquitous and pervasive computing. Within these chapters, the reader is presented with analysis of the most current and relevant conceptual inquires within this growing field of study. Particular chapters discuss ethical issues in pervasive computing, privacy issues, and quality of experience. Overall, contributions within this section ask unique, often theoretical questions related to the study of ubiquitous and pervasive computing and, more often than not, conclude that solutions are both numerous and contradictory. Chapter 7.1. The Ethical Debate Surrounding RFID......................................................................... 1350 Stephanie Etter, Mount Aloysius College, USA Patricia G. Phillips, Duquesne University, USA Ashli M. Molinero, Robert Morris University, USA Susan J. Nestor, Robert Morris University, USA Keith LeDonne, Robert Morris University, USA Chapter 7.2. Privacy Issues of Applying RFID in Retail Industry..................................................... 1358 Haifei Li, Union University, USA Patrick C. K. Hung, University of Ontario Institute of Technology, Canada Jia Zhang, Northern Illinois University, USA David Ahn, Nyack College, USA Chapter 7.3. An Evaluation of the RFID Security Benefits of the APF System: Hospital Patient Data Protection........................................................................................................ 1374 John Ayoade, American University of Nigeria, Nigeria Judith Symonds, Auckland University of Technology, New Zealand Chapter 7.4. Security and Privacy in RFID Based Wireless Networks............................................. 1386 Denis Trček, University of Ljubljana, Slovenia Chapter 7.5. Humans and Emerging RFID Systems: Evaluating Data Protection Law on the User Scenario Basis................................................................................................................ 1396 Olli Pitkänen, Helsinki Institute for Information Technology (HIIT), Finland Marketta Niemelä, VTT Technical Research Centre of Finland, Finland

Chapter 7.6. Privacy Factors for Successful Ubiquitous Computing................................................ 1408 Linda Little, Northumbria University, UK Pam Briggs, Northumbria University, UK Chapter 7.7. Privacy Threats in Emerging Ubicomp Applications: Analysis and Safeguarding....... 1425 Elena Vildjiounaite, VTT Technical Research Centre of Finland, Finland Tapani Rantakokko, Finwe LTD, Finland Petteri Alahuhta, VTT Technical Research Centre of Finland, Finland Pasi Ahonen, VTT Technical Research Centre of Finland, Finland David Wright, Trilateral Research and Consulting, UK Michael Friedewald, Fraunhofer Institute Systems and Innovation Research, Germany Chapter 7.8. Deciphering Pervasive Computing: A Study of Jurisdiction, E-Fraud and Privacy in Pervasive Computing Environment........................................................................... 1450 Grace Li, University of Technology, Sydney, Australia Chapter 7.9. Privacy Control Requirements for Context-Aware Mobile Services............................ 1465 Amr Ali Eldin, Accenture BV, The Netherlands Zoran Stojanovic, IBM Nederland BV, The Netherlands Chapter 7.10. Access Control in Mobile and Ubiquitous Environments........................................... 1481 Laurent Gomez, SAP Research, France Annett Laube, SAP Research, France Alessandro Sorniotti, SAP Research, France Chapter 7.11. Warranting High Perceived Quality of Experience (PQoE) in Pervasive Interactive Multimedia Systems.................................................................................... 1498 Anxo Cereijo Roibás, SCMIS, University of Brighton, UK Chapter 7.12. Pervasive and Ubiquitous Computing Databases: Critical Issues and Challenges................................................................................................................................... 1517 Michael Zoumboulakis, University of London, UK George Roussos, University of London, UK Chapter 7.13. Adaptive Resource and Service Management in a Mobile-Enabled Environment......................................................................................................... 1527 Claudia Raibulet, Universitá degli Studi di Milano-Bicocca, Italy Chapter 7.14. Service-Oriented Architectures for Context-Aware Information Retrieval and Access.......................................................................................................................................... 1549 Lu Yan, University College London, UK

Section VIII. Emerging Trends This section highlights research potential within the field of ubiquitous and pervasive computing while exploring uncharted areas of study for the advancement of the discipline. Chapters within this section highlight ambient learning, ubiquitous games, and new methods for patient monitoring. These contributions, which conclude this exhaustive, multi-volume set, provide emerging trends and suggestions for future research within this rapidly expanding discipline. Chapter 8.1. Ambient Learning.......................................................................................................... 1562 Fernando Lyardet, Technische Universität Darmstadt, Germany Chapter 8.2. Plastic Interfaces for Ubiquitous Learning.................................................................... 1582 José Rouillard, Laboratoire LIFL - Université de Lille 1, France Chapter 8.3. u-City: The Next Paradigm of Urban Development..................................................... 1601 Jong-Sung Hwang, National Information Society Agency, Korea Chapter 8.4. Planning for Knowledge Cities in Ubiquitous Technology Spaces: Opportunities and Challenges............................................................................................................ 1613 Tschangho John Kim, University of Illinois at Urbana-Champaign, USA Chapter 8.5. Emotional Ambient Media............................................................................................ 1626 Artur Lugmayr, Tampere University of Technology, Finland Tillmann Dorsch, Tampere University of Technology, Finland Pabo Roman Humanes, Tampere University of Technology, Finland Chapter 8.6. Leveraging Semantic Technologies towards Social Ambient Intelligence................... 1643 Adrien Joly, Alcatel-Lucent Bell Labs, France & Universite deLyon, LIRIS/INSA, France Pierre Maret, Université de Lyon, France Fabien Bataille, Alcatel-Lucent Bell Labs, France Chapter 8.7. From E to U: Towards an Innovative Digital Era......................................................... 1669 Spyros P. Angelopoulos, Technical University of Crete, Greece Fotis C. Kitsios, Technical University of Crete, Greece Eduard Babulak, Fairleigh Dickinson University, Canada Chapter 8.8. Ubiquitous Services and Business Processes................................................................ 1688 Alistair Barros, SAP Research, Australia Chapter 8.9. Ambient Intelligence on the Dance Floor..................................................................... 1720 Magy Seif El-Nasr, Penn State University, USA Athanasios V. Vasilakos, University of Peloponnese, Greece Chapter 8.10. Adaptive Narration in Multiplayer Ubiquitous Games............................................... 1738 Stéphane Natkin, Conservatoire National des Arts et Métiers, Pans, France Chen Yan, Conservatoire National des Arts et Métiers, Pans, France

Chapter 8.11. Concept of Symbiotic Computing and its Agent-Based Application to a Ubiquitous Care-Support Service............................................................................................... 1762 Takuo Suganuma, Tohoku University, Japan Kenji Sugawara, Chiba Institute of Technology, Japan Tetsuo Kinoshita, Tohoku University, Japan Fumio Hattori, Ritsumeikan University, Japan Norio Shiratori, Tohoku University, Japan Chapter 8.12. Adaptive Awareness of Hospital Patient Information through Multiple Sentient Displays................................................................................................................. 1786 Jesus Favela, CICESE, Mexico Mónica Tentori, CICESE and Universidad Autónoma de Baja California, Mexico Daniela Segura, CICESE, Mexico Gustavo Berzunza, CICESE, Mexico

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Preface

Imagine that your refrigerator can tell you if the food it contains is going bad, or that the clothes you wear can tell your thermostat when to change the temperature in a room. This may seem like the technology of science fiction novels, however, researchers in ubiquitous computing propose this sort of technology and more. Ubiquitous computing is a forward-looking research area which focuses on the integration of technology into everyday life with the end goal of making the technology second nature and nearly, if not completely, invisible to the user. This technology represents a movement away from the current second generation desktop model, in which the user’s interaction with the technology is intentional and deliberate, to a third generation computing model in which the user may engage several technologies at once, possibility without being aware of the interaction. As the world moves closer and closer to the integration of technology into every aspect of life there is a greater need for innovative research and development into the various aspects of ubiquitous computing. Issues surrounding ubiquitous and pervasive computing vary from the practical questions of hardware size and user interfacing to the more ethical questions of privacy and data protection. Every aspect of how users interact with technology and what role technology should play in the world is constantly being reviewed, revised, and updated in light of the ubiquitous computing movement. With such continual change it is important for researchers and practitioners in this field to stay abreast of the latest in technological and theoretical advances. With the constant changes in the landscape of ubiquitous and pervasive computing it is a challenge for researchers and experts to take in the volume of innovative advances and up-to-the-moment research in this multifarious field. Information Science Reference is pleased to offer a three-volume reference collection on this rapidly growing discipline, in order to empower students, researchers, academicians, and practitioners with a wide-ranging understanding of the most critical areas within this field of study. This collection provides the most comprehensive, in-depth, and recent coverage of all issues related to the development of cutting-edge ubiquitous technologies, as well as a single reference source on all conceptual, methodological, technical and managerial issues, and the opportunities, future challenges and emerging trends related to the development of the ubiquitous and pervasive computing model. This collection entitled, “Ubiquitous and Pervasive Computing: Concepts, Methodologies, Tools, and Applications” is organized in eight (8) distinct sections, providing the most wide-ranging coverage of topics such as: 1) Fundamental Concepts and Theories; 2) Development and Design Methodologies; 3) Tools and Technologies; 4) Utilization and Application; 5) Organizational and Social Implications; 6) Managerial Impact; 7) Critical Issues; and 8) Emerging Trends. The following provides a summary of what is covered in each section of this multi-volume reference collection: Section 1, Fundamental Concepts and Theories, serves as a foundation for this extensive reference tool by addressing crucial theories essential to the understanding of ubiquitous and pervasive computing.

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Chapters such as, “Introduction to Ubiquitous Computing,” by Max Mühlhäuser and Iryna Gurevych, as well as “Ubiquitous Computing History, Development, and Scenarios,” by Jimmy Chong, Stanley See, Lily Leng-Hiang Seah, Sze Ling Koh, Yin-Leng Theng and Henry B. L. Duh, provide foundational information on the history of and important topics related to ubiquitous computing. “Understanding RFID (Radio Frequency Identification),” by Susan A. Vowels, presents an explanation of RFID technology and describes how this technology can improve upon the limitations of the barcode system which is already pervasively used for identifying objects. Fariba Sadri and Kostas Stathis present a foundational review of the progress of ambient intelligence research and discuss the role of this technology for independent living in their chapter “Ambient Intelligence.” Ubiquitous computing, pervasive computing, and context computing as they relate to e-commerce are discussed in “Context Related Software Under Ubiquitous Computing” by N. Raghavendra Rao. “Ethical Issues and Pervasive Computing,” by Penny Duquenoy and Oliver K. Burmeister, emphasizes the need for an ethical perspective on the implementation of pervasive technologies and describes a code of professional conduct for consideration while designing and implementing ubiquitous technology. These and several other foundational chapters provide a wealth of expert research on the elemental concepts and ideas which surround the ubiquitous and pervasive computing models. Section 2, Development and Design Methodologies, presents in-depth coverage of conceptual design and architecture to provide the reader with a comprehensive understanding of the emerging technological developments within the field of ubiquitous computing. “Multimodal Software Engineering,” by Andreas Hartl, and “Designing Pervasive and Multimodal Interactive Systems: An Approach Built on the Field,” by Barbara R. Barricelli, Andrea Marcante, Piero Mussio, Loredana Parasiliti Provenza, Marco Padula and Paolo L. Scala, discuss the importance of multimodal technology for pervasive computing and present recommended approaches for the development of these technologies. Heinz-Josef Eikerling and Pietro Mazzoleni present a holistic methodology for the development of context-aware mobile services in their chapter “A Methodology for the Design, Development and Validation of Adaptive and Context-Aware Mobile Services,” while René Meier and Deirdre Lee discuss the iTransIT framework which ultimately leads to a method for creating context-aware ambient services in their chapter “Context-Aware Services for Ambient Environments.” From chapters covering a broad description of developmental concepts, such as Varuna Godara’s “Pervasive Computing: A Conceptual Framework,” to chapters describing the use of pervasive technologies to deal with a specific question, as in “A Mandarin E-Learning System in Pervasive Environment” by Yue Ming and Zhenjiang Miao, this section provides a vast array of methods and approaches to designing relevant and useful ubiquitous technologies. With more than 20 contributions from leading international researchers, this section offers copious developmental approaches and methodologies for ubiquitous and pervasive computing. Section 3, Tools and Technologies, presents extensive coverage of the various tools and technologies used in the development and implementation of ubiquitous and pervasive technologies. This comprehensive section includes chapters such as “An Intelligent Wearable Platform for Real Time Pilot’s Health Telemonitoring,” by Christos Papadelis, Chrysoula Kourtidou-Papadeli, Fotini Lazaridou and Eleni Perantoni, as well as “A SCORM Compliant Courseware Authoring Tool for Supporting Pervasive Learning,” by Te-Hua Wang and Flora Chia-I Chang, which describe pervasive technologies developed with niche specific practical uses in mind. “Ubiquitous Computing Technologies in Education,” by Gwo-Jen Hwang, Ting-Ting Wu and Yen-Jung Chen, describes potential issues surrounding the implementation of ubiquitous and mobile technologies in e-learning. The EMURCT system to assist with randomizing circuit training programs in an effort to keep trainees from becoming bored with their workout is described in “Electronic Multi-User Randomized Circuit Training For Workout Motivation” by Corey

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A. Graves, Sam Muldrew, Tiara Williams, Jerono Rotich and Eric A. Cheek. Authors Artur Lugmayr, Alexandra Pohl, Max Müehhäueser, Jan Kallenbach and Konstantinos Chorianopoulos describe ubiquitous technology for domestic use in home entertainment systems in their chapter “Ambient Media and Home Entertainment.” With more than a dozen additional contributions, this section provides coverage of a variety of tools and technologies under development and in use in the ubiquitous and pervasive technologies community. Section 4, Utilization and Application, describes the implementation and use of an assortment of cutting edge ubiquitous technologies. Including more than 25 chapters such as “Motorola’s Experiences in Designing the Internet of Things,” by Andreas Schaller and Katrin Mueller, and “To Connect and Flow in Seoul: Ubiquitous Technologies, Urban Infrastructure and Everyday Life in the Contemporary Korean City,” by Jaz Hee-Jeong Choi and Adam Greenfield, this section provides insight into the application of ubiquitous technologies for both professional and private use. “Using RFID to Track and Trace High Value Products: The Case of City Healthcare,” by Judith A. Symonds and David Parry, describes the replacement of barcodes with RFID tags by City Healthcare of New Zealand and the implications, benefits, issues and challenges associated with that change. The application of ubiquitous technology to the healthcare field is also discussed in “An Ambient Intelligence Based Multi-Agent System for Alzheimer Health Care,” by Dante I. Tapia and Juan M. Corchado, as well as “RFID as the Critical Factor for Superior Healthcare Delivery,” by A. Dwivedi and T. Butcher. The practical use of handheld devices for accessing digital library materials is described in “Handhelds for Digital Libraries” by Spyros Veronikis, Giannis Tsakonas and Christos Papatheodorou. Contributions found in this section provide comprehensive coverage of the practicality and present use of ubiquitous technologies. Section 5, Organizational and Social Implications, includes chapters discussing the impact of ubiquitous technology on social and organization practices. Chapters such as “Consumer Attitudes toward RFID Usage,” by Madlen Boslau and Britta Lietke, as well as “Adapting to the User,” by Matthias Jöst, focus on the attitude and acceptance of individuals interacting with and using ubiquitous technologies. “How Research can Help to Create Commercially Successful Ubiquitous Services,” by Teea Palo, Kaisa Koskela, Timo Koivumäki and Jaana Tähtinen, stresses the importance of research to the implementation and successful marketing of ubiquitous services. The impact of ubiquitous technology on education and learning environments is discussed in chapters such as “Collaborative Technology Impacts in Distributed Learning Environments,” by Martha Grabowski, Greg Lepak and George Kulick, and “Learning by Pervasive Gaming: An Empirical Study,” by Christian Kittl, Francika Edegger and Otto Petrovic. B.K. Mangaraj and Upali Aparajita, in their chapter “Cultural Dimension in the Future of Pervasive Computing,” advocate the importance of a cultural focus when considering the introduction of a ubiquitous technology in order for the technology to be accepted and successful. Section 6, Managerial Impact, presents a focused coverage of ubiquitous computing as it relates to improvements and considerations in the workplace. Varuna Godara’s chapter “Pervasive Business Infrastructure: The Network Technologies, Routing and Security Issues” provides an overview of pervasive business technology and discusses related business concerns such as confidentiality and authenticity. “Intelligent Supply Chain Management with Automatic Identification Technology,” by Dong Li, Xiaojun Wang, Kinchung Liu and Dennis Kehoe, proposes RFID-enabled business models for implementation in supply chain management. Also focusing on the application of ubiquitous technology to supply chain management is “RFID and Supply Chain Visibility” by Sumeet Gupta, Miti Garg, Heng Xu and Mark Goh, which discusses the adoption of RFID technology for supply chain visibility while reviewing related issues. J. Ramsay, M. Hair and K. V. Renaud in their chapter, “Ubiquitous Connectivity & Work-Related Stress,” present a study of e-mail usage by workers and describe their findings in relation to the changes in work place stressors over the last 25 years.

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Section 7, Critical Issues, addresses vital issues related to the ubiquitous computing model such as privacy, access control, and data protection, among others. Chapters such as Denis Trček’s “Security and Privacy in RFID Based Wireless Networks” and “Privacy Issues of Applying RFID in Retail Industry,” by Haifei Li, Patrick C. K. Hung, Jia Zhang and David Ahn, tackle the difficult question of privacy and data security for the application of RFID technology. In “Invisibility and Visibility: The Shadows of Artificial Intelligence,” by Cecile K. M. Crutzen and Hans-Werner Hein, the authors discuss the construction of new meanings relating to human computer interaction as the visible action of users will be both preceded and followed by the invisible action of intelligent technology. “Pervasive and Ubiquitous Computing Databases: Critical Issues and Challenges,” by Michael Zoumboulakis and George Roussos, provides an explanation of the importance of databases to the ubiquitous and pervasive computing movements. Ambient information displays and issues related to their evaluation are discussed in “Issues for the Evaluation of Ambient Displays” by Xiaobin Shen, Andrew Vande Moere, Peter Eades and SeokHee Hong. The chapter “IPML: Structuring Distributed Multimedia Presentations in Ambient Intelligent Environments,” by Jun Hu and Loe Feijs, discusses the IPML markup language as an answer to issues relating to distributing multimedia presentations in ambient intelligent environments. These and other chapters in this section combine to provide a lively review of those issues which are most important to ubiquitous and pervasive computing technologies. The concluding section of this authoritative reference tool, Emerging Trends, highlights areas for future research within the field of ubiquitous computing, while exploring new avenues for the advancement of the technology. Jong-Sung Hwang’s chapter, “u-City: The Next Paradigm of Urban Development,” describes South Korea’s u-City project. The project is based on an emerging concept that uses ubiquitous technology to provide innovative urban services. “Voices from Beyond: Ephemeral Histories, Locative Media and the Volatile Interface,” by Barbara Crow, Michael Longford, Kim Sawchuk and Andrea Zeffiro, describes the emerging technology and theories used by the Mobile Media Lab in two of their recent projects. José Rouillard describes his research into the delivery of content via heterogeneous networks and devices resulting in the adaptive pervasive learning environment PerZoovasive. The description and results of his research project can be found in the chapter “Plastic Interfaces for Ubiquitous Learning.” The state of research into next generation Internet and telecommunications technologies, as they relate to a variety of research projects such as Future House 2015, can be found in the chapter “From E to U: Towards an Innovative Digital Era” by Spyros P. Angelopoulos, Fotis C. Kitsios and Eduard Babulak. In his chapter “Life in the Pocket: The Ambient Life Project Life-Like Movements in Tactile Ambient Displays in Mobile Phones,” Fabian Hemmert presents the results of his study in which ambient displays are used to notify users of missed events on their mobile phones. These and several other emerging trends and suggestions for future research can be found within the final section of this exhaustive multi-volume set. Although the primary organization of the contents in this multi-volume work is based on its eight sections, offering a progression of coverage of the important concepts, methodologies, technologies, applications, social issues, and emerging trends, the reader can also identify specific contents by utilizing the extensive indexing system listed at the end of each volume. Furthermore to ensure that the scholar, researcher and educator have access to the entire contents of this multi volume set as well as additional coverage that could not be included in the print version of this publication, the publisher will provide unlimited multi-user electronic access to the online aggregated database of this collection for the life of the edition, free of charge when a library purchases a print copy. This aggregated database provides far more contents than what can be included in the print version in addition to continual updates. This unlimited access, coupled with the continuous updates to the database ensures that the most current research is accessible to knowledge seekers.

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Although the concept of ubiquitous and pervasive computing may once have been the imaginative fodder of science fiction writers and readers alike, it is fast becoming a technological reality. This model of computing continues to grow and thrive as researchers and practitioners rethink the way that we interact with and understand the role of technology in everyday life. As ubiquitous technology becomes more and more of a reality, the demand for thorough integration, smaller hardware, and thoroughly invisible technology will continue to grow. The move from second generation desktop computing to the third generation ubiquitous model is certain to increase the demand for greater improvements and cutting edge research in RFID, ambient intelligence, and other areas related to the advancement of ubiquitous computing. Access to the most up-to-date research findings and firm knowledge of proven techniques and models from other researchers and practitioners of the ubiquitous computing model will facilitate the discovery and invention of increasingly more effective methods and technologies. The diverse and comprehensive coverage of ubiquitous and pervasive computing in this three-volume authoritative publication will contribute to a better understanding of all topics, research, and discoveries in this developing, significant field of study. Furthermore, the contributions included in this multi-volume collection series will be instrumental in the expansion of the body of knowledge in this enormous field, resulting in a greater understanding of the fundamental concepts and technologies while fueling the research initiatives in emerging fields. We at Information Science Reference, along with the editor of this collection and the publisher, hope that this multi-volume collection will become instrumental in the expansion of the discipline and will promote the continued growth of all aspects of ubiquitous and pervasive computing.

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Ubiquitous and Pervasive Computing:

Concepts, Methodologies, Tools, and Applications Judith Symonds Auckland University of Technology, New Zealand

IntroductIon A lot of people around the world are interested in ubiquitous computing. If you are reading this, then perhaps you are too. Many, many different applications have been developed around through three decades. Some areas seem to be developing faster than others. My colleague, Associate Professor Jeffrey Soar from the University of Southern Queensland pointed out to me one day that ubiquitous technologies in cars are far more developed than ubiquitous home technologies. Being a studious, young and perhaps overly eager to please, I didn’t take Prof. Soar at his word. I investigated the situation and in this chapter I write about my findings and relate them to an overview of pervasive and ubiquitous computing. Hopefully, this chapter provides a thought provoking and intriguing introduction to this multi-volume set on pervasive and ubiquitous computing. I start this chapter thinking about the following question: Is automobile technology more ubiquitous than home technology and if so, why is this so?

Motivation Why is this an important question? What will be gained if we know the answer to this question? Currently, many aspects of ubiquitous computing are the domain of enthusiasts. Enthusiasts push the development forward in pockets. However, for true transformation, a broader approach is needed. If we can understand what is driving forward the development of ubiquitous applications in one vertical sector, then perhaps we can work out ways to encourage development in other sectors. To understand the aspects of technology better, let’s look at the Technology Adoption Lifecycle (Figure 1). Current smart home implementations are innovators & early adopters. As more and more innovators develop home automation applications, we can expect to find that the ideas penetrate the market to the

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Figure 1. Technology adoption lifecycle

early and late majority. There are some companies who cater to certain buyers and who specialise in home automation such as Kristil in New Zealand (http://www.kristil.co.nz/home.html). However, currently, the automation technology implemented centres around climate control, security and entertainment systems. These home automation systems do not yet know whether the user is home or not for example which would be an important functionality of full home automation. The 2007 Hack A Day overall winner was shifd (shifd.com) which essentially involved a mobile phone and a laptop and automatically shifting information from one device to the other based on whether the user is home or not. Their crude test of whether the user was home or not was to use an RFID tag and a RFID reader set up as a cradle to tell if the user was home or not. If the RFID reader detects that mobile phone, then the system assumes that the user is home. Notice, that I said ‘crude’ as this system does not allow for people who leave their mobile phone by accident, like me. (Hack A Day is a 24 hour competition and this results in ‘quick and dirty’ conceptual creations often based on impossible dreams.) The concept of the shiftd application was that when at home, the user could queue things to look at later such as the location of a coffee shop on google maps ready to be downloaded to the mobile phone. As soon as the system sensed that the phone was away from home (i.e., out of range of the RFID reader in the cradle), information was downloaded to the mobile phone. The opposite is also true in that an email address could be added to the phone during coffee and then uploaded to the user email box from the phone when the system recognises that the user has returned home (i.e., the phone is replaced in the cradle). Another application of sensing if the user is home or not can be seen in the use of naked DSL and VOIP in the home where the mobile phone can detect that it is as ‘home’ and make use of the home connection, while only using cell phone technology when away from ‘home,’ thus saving the user money on mobile phone bill payments. The same could be used for WAP Internet browsing where the WAP is only used with the phone is away from ‘home.’ Can a modern car sense that the driver is there? Well, I guess the concept is much easier as the key being inserted in the ignition of the car signifies that the user is in the car and likewise, the key being taken from the ignition perhaps signifies that the user is leaving the car. However, leaving the key in the ignition and opening the driver side door will cause the car to alarm as these are conditions that can lead to the driver locking their key inside the car. Final central locking of the car probably signals best that the user is leaving the car.

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Probably the main motivation behind checking that when the drive side door is open, the key is removed from the lock is that driver lockouts can be a major cause of driver stranding. According to the AA in the United Kingdom, driver lockouts and accidental vehicle immobilisation are the two fastest rising reasons for calling for assistance (source: http://www.breakdowncover.co.uk/) This is not to say that being locked out of your own home is not a similar hazard. However, driver lockouts are recorded by roadside assistance companies such as AAA and such organisations have considerable influence over vehicle manufactures as they also perform other roles such as new vehicle testing and reviews. There isn’t the same level of call-out assistance for being locked out of home. While being stranded outside your own home is frustratingly, hair pulling-outly annoying, it isn’t quite as dangerous as being stranded on the side of a motorway or even worse, a dusty isolated track in the Northern Territories of Australia. Also, electronically ‘knowing’ whether the user is about to lock themselves out of the house is infinitely more complex for the house situation because many house systems mean that you lock the mechanism from inside and then pull the door shut. Or alternatively, in the case of a standalone building with an internal car garage, you flick the automatic car garage door switch to start the door closing while you slip out under the closing door. It may be that the simplest way around this is to create a house ignition. The home owner comes home, opens the garage door with the wireless garage door key and then inserts a key into the home ignition to signify that the user is home. This could signal many electronic processes like the water heater, fridge and freezer powering up ready for the prospect of hot water being consumed and fridge doors being opened, hence requiring more power to refrigerate to the same level as when there is no one home using hot water and opening the fridge door to let in hot air or placing relatively warm shopping contents in the fridge to be cooled. This system would also deactivate the iron, portable heater and the cook top before leaving. This discussion has outlined the motivations of this chapter. It is useful now to move on and consider a definition of ubiquitous computing to provide a scope for this discussion.

ubIquItous coMputIng defIned It is important to define what is meant by ubiquitous and pervasive computing before continuing. First, I looked at a couple that caught my interest: Ubiquitous Computing: Computing that is omnipresent and is, or appears to be, everywhere all the time; may involve many different computing devices that are embedded in various devices or appliances and operate in the background. (source: http://www.mansfieldct.org/schools/mms/palms/Meet_the_Team/Glossary.htm) Ubiquitous Computing: The practice of making computers so common and accessible that users are not even aware of their physical presence. The ideal of ubiquitous computing could be defined as a high-speed network that covers any kind of geography and is easily installed and automatically maintained. (source: http://substratum.ca/subs/Resources/TechTerms/?letter=U) Ubiquitous Computing (ubicomp): is a post-desktop model of human-computer interaction in which information processing has been thoroughly integrated into everyday objects and activities. (source: http://en.wikipedia.org/wiki/Ubiquitous_computing)

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The age of calm technology, when technology recedes into the background of our lives. (source: http://www.ubiq.com/hypertext/weiser/UbiHome.html ) Ubiquitous computing: An integration of microprocessors into everyday objects like furniture, clothing, white goods, toys even paints. (Alcaniz 2005, p. 3) (source: https://igi-pub.com/downloads/excerpts/reference/IGR6314.pdf) I identify most with the definition of calm computing given by Mark Weiser. I also like the idea of technology being omnipresent and everywhere which seem very similar to Weiser’s use of the term ‘background.’ All the other definitions seem to show pieces of the management elephant; embedded computing devices, high-speed networks that are everywhere and the meeting of mobile intelligent devices with everyday objects such as furniture and clothing. This gives a very wide scope, which is probably very necessary. Much about the extension of digital computing to digital objects is still unknown.

sMart thIngs Some work on digital objects is carried out by ‘Things That Think’ (source: http://ttt.media.mit.edu/vision/vision.html) at MIT in Cambridge in the USA. Things That Think Co-Directors Professors Hiroshi Ishii, Joe Paradiso & Roz Picard put forward three themes of research on smart things: 1. Research into sophisticated sensing and computational architectures that augment, animate and coordinate networks of things; 2. Research into seamless interfaces that bridge digital, physical and human perspectives; 3. Research into an understanding about what makes things think at a much deeper level. Some thinking has already occurred around the first theme of networks of things by the Auto ID Centre. The centre came up with the concept of the internet of things. This poetic description can be expressed as the building of a global infrastructure for RFID tags. You could think of it as a wireless layer on top of the Internet where millions of things from razor blades to euro banknotes to car tires were constantly being tracked and accounted for. A network where, to use the rhetoric of the Auto ID Centre, it is possible for computers to identify “any object anywhere in the world instantly.” (source: http://www.guardian.co.uk/technology/2003/oct/09/shopping.newmedia) The second research theme is considered by the Oxygen project. The lofty goal of the project, funded partly by the Defense Advanced Research Projects Agency, is to create a new computing environment, in which computer firepower would be ubiquitous and manipulating computers as easy for people as breathing. Oxygen researchers want people to throw away the mouse and talk to their computers, some of which, researchers suggest, would be embedded in walls and ceilings (source: http://www.sfgate.com/ cgi-bin/article.cgi?file=/chronicle/archive/2004/11/22/BUG719UPI31.DTL&type=business ). Such a prospect would give new meaning to the idea that the walls have eyes and ears. The third research theme of having a much deeper understand of what makes digital things think is perhaps addressed by the concept of Digital Object Memories proposed at a workshop on Digital Object Memories (source: http://www.dfki.de/dome-workshop) by Michael Schneider at the Intelligent Environments Conference. Schneider proposes that Digital Object Memories“comprise hardware and software components that physically and/or conceptually associate digital information with real-world objects in an application-independent manner.” The significance of this work is that over time, digital objects can build up a meaningful record of an object’s history and use. Such information could lead to discoveries about how objects can think.

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faMous applIcatIons One of the earliest ubiquitous systems was artist Natalie Jeremijenko’s “Live Wire”, also known as “Dangling String,” installed at Xerox PARC during Mark Weiser’s time there. This was a piece of string attached to a stepper motor and controlled by a LAN connection; network activity caused the string to twitch, yielding a peripherally noticeable indication of traffic. Weiser called this an example of calm technology. More recently, Ambient Devices has produced an “orb,” a “dashboard,” and a “weather beacon”: these decorative devices receive data from a wireless network and report current events, such as stock prices and the weather.

systeMs developMent Recent developments in the ubiquitous computing area in terms of systems development show momentum building for AmI (Ambient Intelligent systems development) (source: https://igi-pub.com/downloads/ excerpts/reference/IGR6314.pdf The ambient intelligence paradigm builds upon ubiquitous computing, profiling practices and humancentric computer interaction design and is characterized by systems and technologies (Zelkha & Epstein 1998) that are: • • • • •

embedded: many networked devices are integrated into the environment context aware: these devices can recognize you and your situational context personalized: they can be tailored to your needs adaptive: they can change in response to you anticipatory: they can anticipate your desires without conscious mediation.

Ambient intelligence is closely related to the long term vision of an intelligent service system in which technologies are able to automate a platform, embedding the required devices for powering context aware, personalized, adaptive and anticipatory services. A typical context of ambient intelligence environment is a Home environment (Bieliková & Krajcovic 2001). Maybe mobile phones will form an integral part of this environment, controlling other networked devices that are integrated into the environment. Source: http://www.ercim.org/publication/ Ercim_News/enw47/bielikova.html Wiser & others originally envisioned a world where we would have many different computers that represent different functionalities. That is, Wiser’s vision was many computers for each person. However, the convergence of personal devices has given rise to the ubiquitous mobile which functions as a phone, voice recorder, music player, camera and game console, among other things. Simon Andrews (www.mindshareworld.com) writes that mobile phones are central to many aspects of people’s lives and they are a key access point to all media uses (refer to Table 1). One futuristic representation of family activities in the home related to ubiquitous computing (source: http://www.at.capgemini.com/m/at/ tl/2016_The_Future_Value_Chain.pdf) shows only one application not deliverable via mobile phone. In the example, the milk carton ‘beeps’ to signal that it is below temperature and needs to be replaced to the fridge. Currently this functionality can be seen on the side of fresh-up juice bottle containers that include a motif that changes colour when the juice is chilled. All of the other functionalities in the example can be delivered via mobile phone such as a message to say that the weekly grocery order is due for collection, test results, and bus time-table information.

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Table 1. Mobile motivation (Source http://www.istart.co.nz/index/HM20/PC0/PVC197/EX245/ AR211048) MOBILE MOTIVATION Below are the five key motivations behind technology use. The mobile phone is a platform to all of them. Motivation

Mobile Function

Information

Mobile internet access, location-based services

Entertainment

Music storage/services, mobile gaming, mobile TV

Communication

Voice, SMS, IM, email

Transaction

Mobile internet, barcode coupons, swipe & pay

Self expression

Handset ‘look’, ringtones

developMent approach to ubIquItous coMputIng Mark Wiser and friends first began experimenting with pervasive devices at the auto-id lab by trying to make the devices that they envisioned. This development approach favours a Design Science research approach. Innovative ubiquitous computing artefacts often seem to come from working with simpler technologies. Microprocessor technologies such as PICAXE microprocessors and Audino kits encourage research students to experiment with the technology in new ways. Arduino is an open-source electronics prototyping platform based on flexible, easy-to-use hardware and software. It’s intended for artists, designers, hobbyists, and anyone interested in creating interactive objects or environments. Low cost microprocessors (PICAXE kits cost under $NZ50 to purchase) give researchers an easy way to manipulate computer equipment in new ways. Many fabulous ubiquitous computing ideas have arisen from hack day competitions. Microsoft recognises the importance of the hack day concept and runs a similar program called the imagine cup. Hack day organisers simply run a kind of ‘byo’ party where the participants bring any old hardware lying around their offices such as old keyboards, mobile phones and dance pads. Examples of hack day projects include being able to txt a VCR to be able to tape a program while the owner remains away from the home. Done with a virtually worthless VCR and 2nd Generation mobile phone, the outcome is clunky and still requires the user to have had the presence of mind to leave a suitable cassette in the player before leaving the house in the morning. However, with the introduction of high definition free to view TV with a hard disk embedded in the decoder, the ability to use a txt to book a movie or to record a favourite television program remotely becomes all that much more likely. Many new ubiquitous computing developments are being played out in Second Life. Developments in Second Life, the virtual reality world game, are not restricted by the availability of hardware. School children are able to use the high level scripting languages to quickly develop any concept. Universities have their own areas in Second Life and even lectures can be help in Second Life. Virtual reality environments such as Second Life are perfect for trying out development and ubiquitous worlds without being constrained by reality. However, virtual reality computing is not ubiquitous computing. Ubiquitous environments are everything that virtual environments are not. However, there is a very interesting crossover between the environments. Companies like Right Hemisphere in Auckland, New Zealand develop sophisticated visual design software that can interpret a high specialised design in virtual reality into a physical prototype. (source: http://www.righthemisphere.com ). The virtual work that Right Hemisphere does integrates back into real world objects such as televisions and even electronic docu-

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ments where virtual software can allow the user to use a mouse to turn an image of an object around as though it were three dimensional. Ubiquitous computing development is constrained by what the hardware developers know will sell. RFID interrogators embedded in mobile phones are a good example. Nokia released the first one in 2004. Unfortunately, at that time the infrastructure to allow customers to use the technology was not present and so RFID embedded phones did not go past the first release. Open source software development is an important aspect of ubiquitous computing development. Often ideas are launched from others and only by seeing others work, new conclusions are reached and developments are improved with each cycle of use. Similar to the ideals of open source software, service oriented architecture allows ubiquitous computing researchers to develop applications which can be used in many different ways and applications. Many ubiquitous computing research problems lend themselves to a design science research approach. Design science uses a problem based approach to the design and development of artefacts. This research approach ensures that the artefact is scientifically tested and evaluated as well as placing strong emphasis on the problem solving aspects of research (Hevner, March, Park & Ram 2004). In order to be successful, ubiquitous computing systems must also be accepted by human users and therefore, there are essentially two streams of research in this area: 1. Technology acceptance work which looks at influencing factors such as ease of use and perceived usefulness (Venkatesh & Davis 2000) and 2. Usability testing of specific pervasive devises and services (Nielsen 1992). Much of the development of pervasive systems originates from the hobby field from people who like to build and invent things. In this regard, there are also books of projects such as RFID toys (http:// www.rfidtoys.net/) which provide samples of different project ideas to experiment with and try. Projects included in RFID toys include digital bookshelves that can track the addition and removal of books and keep a report of borrowers. You can even create a pet door that unlatches only when you pet approaches and not when other neighbour’s cats approach for example. This application can also be helpful if you live in a very cold environment and you want to have the door unlatched only when the pet enters and not when a cold wind blows through. Apart from hobby toys with neat outcomes, as suggested by the title ‘RFID toys’ as in play things, there are other researchers who build things out of a problem. Take, for example, the work of AUT student Doug Hunt (http://www.slideshare.net/jsymonds/doug-hunt) who encountered a problem with providing unobtrusive feedback to equine dressage riders about the position of the wrists. The position of the wrists is crucial in dressage riding as the wrong position can impact on the rider’s ability to stop the horse and to communicate sensitively to the horse. Doug has designed a device to be worn on the wrist of the rider that provides unobtrusive feedback to the rider about the position of the hands and wrists and also captures data for later retrieval. Doug has trialled this device with many equestrian riders and developed several prototypes of his design. One way of evangelising the new pervasive environment in the business world is to build a demonstrator–a space where examples of new technology that still have ‘toy’ like properties in that a real business need has not yet been made can be installed to scale and can be viewed working. One example of such a system for RFID can be seen at http://itri.uark.edu/rfid.asp. Called the RFID Research Centre, this real life demonstrator has a number of parts showing different organisational aspects of the supply chain including the delivery dock, the conveyor belt, the warehouse and the shop floor. At the technological development end of the field, researchers rely on development prototype platforms to provide infrastructure on which to conduct developmental work. For example, Intel’s Wireless Identification and Sensing Platform (WISP) where researchers are working on ways that RFID chips

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can do complex calculations in short bursts when the passive tags are powered up by a RFID reader (Anderson 2009).

ubIquItous coMputIng applIcatIons Ubiquitous Computing is considered across a wide range of application areas. These include commerce, management, health, security, personalisation, education and smart environment applications.

u-commerce U-commerce (ubiquitous commerce) is an extension of digital e-commerce. Initial examples include using mobile phone sms messages to pay for car parking and other small items (i.e., vending machine purchases) using a mobile phone account. Next generation u-commerce will likely involve the use of NFC (Near Field Communication) embedded into a mobile phone to pay for services ubiquitously, such as purchasing event tickets as you pass through the front gate of the event. Watson, Leyland, Berthon and Zinkhan (2002) suggest that the best way to envision u-commerce is on a scale of embeddedness and mobility as shown in Table 2. We are currently at least one decade out from seeing any true u-commerce. Junglas & Watson (2003) predict that the capability maturity steps for u-commerce will be similar to the number of letters in the alphabet between each step. That is, five steps to ‘E’ – e-commerce, eight steps to ‘M’ – ,m-commerce and eight steps to ‘U’ – u-commerce

Management Aggregated Internet nusiness models, increased supply chain visibility enabled through increased tracking and traceability ability, and contactless payment will have a lasting effect on the future value chain (source: http://www.at.capgemini.com/m/at/tl/2016_The_Future_Value_Chain.pdf ). The key industry trends likely to impact the value chain are consumer behaviour, information flow and product flow.

network Management Some researchers have estimated that there are more than 10 billion wireless sensors deployed in diverse applications including environmental monitoring, agricultural monitoring, machine health monitoring, surveillance and medical monitoring. These networks of wireless sensors connect the physical world with the digital world. However, the current wireless networking infrastructure that allows for support of wireless sensor communication is going to be overloaded with connecting so many sensors. Therefore, the very important work of Associate Professor Wendi Heinzelman of the Electrical and Computer Engineering Department at the University of Rochester will be groundbreaking in facilitating such Table 2. U-commerce embeddedness and mobility Embeddedness

Pervasive

Ubiquitous

Traditional

Mobile

Mobility

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communication between the wireless sensors and the digital world. The work is in adaptive network management to support dynamic mapping and the use of network aware architectures.

personalisation A new era has just started in many homes around the world with the first consumers having access to on demand high definition television. This allows consumers, for the first time, to control the programming and availability of television programs. It also allows the user to be able to pause the program as though they were watching their own personal copy of the television program. Personalisation has been spurred by consumer access to the World Wide Web and mobile phones. A popular Internet business model is to create personalise products via the World Wide Web. For example, it is possible to customise your own pair of sports shoes. In many ways the mobile phone is actually replacing the home phone. Home phones are shared and the caller uses one number to effectively access a household and then to further ask to speak with one particular individual. However, a mobile phone number reaches a specific individual. Therefore, with a mobile phone number, marketing companies can be sure to be speaking to the right person. Mobile phone users have the ultimate ability to personalise their advice choosing the colour of their device, the wallpaper on their display screen, the phone numbers in their address book and the functionality of their individual device. I am proud to lead a team of researchers in a Health Research Council of New Zealand feasibility study developing a personalised intelligent prompt to help people affected by Traumatic Brain Injury in their recovery. The device automates a process called Goal Management Training which would normally be done using traditional methods of creating a poster or an instruction booklet with simple steps for everyday tasks that are relevant to the patient such as the steps for getting dressed each day. Carers can then help the patient through these steps. By automating this process with a personalised device, we are empowering the patient to be more independent and hence complete more tasks without the help of a carer and we are supporting the important aspect of errorless learning while also providing only the right amount of prompting to encourage the patient to think for themselves and to begin to get the brain neurons and pathways firing again. When a carer helps, the process of recovery is so slow for brain injury patients that the carer may develop a habitual approach to prompting the patient and may not be patient enough to encourage brain development. A personal device is patient and not governed by habitual approaches. Each time the patient attempts the task with a digital device, there is no history based on previous habits, performance or happenings.

education I recently heard about a project in the United States where researchers had deployed sensors in a pond. The sensors record water temperature, quality and level and are wirelessly enabled to report the information that they collect back to an application which then will be made accessible via the World Wide Web. The information is intended for one group of scientists; however, the information is available to many different users of the World Wide Web including school groups who can use the data to inform their own studies on ecosystems. Not all of the research need be conducted online, the students can experiment with collecting their own data at a real pond, and they can aggregate this with the data from the World Wide Web which is longitudinal and scientific. They can also join with other school groups to exchange this information. Perhaps there are many other examples of pervasive information that would have immense education benefits. We can see this trend happening a little already with many museums and science centres already using pervasive systems to enhance the educational value for visitors. For

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example, many multimedia displays can be activated by the participants themselves using their mobile phone and therefore, the user can interact much more individually with the information linked to the exhibit and manipulate the presentation on their own personal device rather than being played a static multimedia display on in a shared presentation space.

Office Applications Most office buildings use electronic RFID cards to access the building. In the case of a university, that card will be used to access lecture rooms, meeting rooms and specific areas of the building. Although most of the reader devices are effectively dumb and contain no microprocessing ability at all, it is possible to capture all information from the cards of entry access by individual cards. Using current technology, the information captured would then need to be aggregated with other information from the database that tracks the issue of cards to be able to draw up a high level tracking database information. Managers could then tell arrival and departure times at work and also how prompt that lecturer was to a class and also how long the lecture stayed. With more information about the user other than the unique identification number, this information will be able to be drawn up more quickly. One interpretation of such invasive data may be that this information is unhelpful. However, there is a much more helpful interpretation of this information such that as the lecturer approaches the lecture room, the computer is already logged on for them and the room is already configured as they would like it (lighting and so on). This could also happen in conference rooms. At Microsoft Research in India, a project of this type is being undertaken. The project is called Sixth Sense (Ravindranath, Padmanabhan & Agrawal 2008) which seeks to build what is called an ‘Enterprise Intelligence.’ The researchers at Microsoft Research India have been working on a pervasive work environment that uses RFID and other technologies to aggregate data about the employees. This information base serves as an infrastructure onto which the team has started work on applications that use the data to created intelligent systems. One application they built to showcase the ambient information that they had collected was the semi-automated image catalog which allowed users to take photos and then cataloged the image according the where the image was taken. The image catalog is itself adding to the infrastructure of data that is being built up that would allow still other applications to replace the unique identification number of an object with a picture of it in its natural place in the office. The second application that they built was an automated conference room booking system which could identify participants in the room and if they intended to stay, check for a booking, advise of a booking clash or place a booking to indicate that the room is in use. Teleworking has long been part of an ideal virtual world where office space can be minimised by having employees work from home for some part of their working week and share a hot-desk for the other days (Emily uses the hot-desk on Monday & Tuesday and Helen uses the hot-desk on Wednesday, Thursday and Friday). Alternatively, workers have access to a pool of generic consulting rooms where workers book any of the rooms or desks for the days that they are in the office. However, this becomes a very cold and sterile environment to work in. Therefore, if the employee card could identify them as they walk into the office, it could cause the desk to configure to their preferences. Emily’s photos could be displayed in the digital photo frame when she arrives in the room and her computer could sense her arrival and automatically log on and configure with her preferences. This phenomenon is a daily reality in the doctor/patient consulting practice. The traditional model is that each doctor occupies a room and the patients are summoned in by the doctor for each consult. However, where the number of consultations that a doctor can perform everyday translates into the amount of money the doctor or the practice can earn, people are always looking for new approaches. It is much more efficient to have the doctor visit the patients in different rooms. This approach is used in emergency rooms and in some centres. However,

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the doctor now has to work with a generic set of medical equipment, stationery and even a generic desk and chair. However, more intelligent environments could help to make the doctor more comfortable by customising the settings in the room according to their preferences whenever they use that room based simply on the event of their employee proximity tag coming through the door of the consulting room. I have thought about my own application that I would build using Ravindranath, Padmanabhan & Agrawal’s (2008) infrastructure. It’s a pervasive meeting schedule assistant. Being Mum means cut throat time management. Being Mum also means that when I am coming in to the office specifically for a meeting, sometimes I end up being 5-10 minutes late. The clock in my car is permanently set 10 minutes fast. However, this doesn’t work because I know it is 10 minutes fast and I spend time making calculations back and forth and wishing that the clock was another 10 minutes faster. This pervasive meeting schedule assistant would be intelligent enough to know my appointments and my location. Assuming that I have a 10:00am appointment with Bethany, it would work like this: 1. 2. 3. 4. 5.

9:55am check my location – am in the office? If no, use location information to work out where I am (this would involve a wider location aware system based on cell phone networks perhaps). Calculate time to walk from location to office based on historical personal information gathered each day. Access Bethany’s details from my address book. SMS Bethany to notify her that I am a 5 minute walk away.

Currently, I tend to either try to stop the car along the way to make the text message. Alternatively, I try to walk and text, which uses up less time, but is not efficient because usually as I glance up, predictive txt ends up typing something different and I have to delete several characters to fix it, causing more stress. The alternative is attractive to me; I can know that I am late, but also know that the assistant will text my appointment and let them know to wait for me. I can drive uninterrupted to my parking space, and walk to my office taking a few deep breaths and mentally prepare for the meeting.

securIty In a pervasive environment, it is becoming more and more likely that there will be many different sensors, RFID tags and other small smart microprocessor controlled devices. If such devices are effectively accessed by any wirelessly enabled device and there is personal information stored on that device, then there will be a need for heightened levels of security. To illustrate the problem, any wireless computer can currently sense any wireless network within the vicinity of the device. On many occasions, I have noticed that a wireless network is not protected by authenticated access and although it would be unethical to do so, it is possible to access the Internet through that network without incurring a service charge. Imagine an environment where there are at least many thousands of smart microprocessor controlled devices that do tasks from sensing temperature, air quality, and noise level and record this information locally for access later by other devices. Clearly access to such information must be controlled. In my recent work with colleague John Ayoade (Ayoade & Symonds 2009), we have explored this problem specifically related to data-on-tag RFID systems by developing a prototype using a two level security system. Firstly, the application ensures that only authentic/registered devices and users are able to connect to the application and therefore the ability to read data from the tag is restricted. Secondly,

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Figure 2. Pervasive computing privacy continuum Irrational Hysteria

Ignorance

Ambivalence

New Development

Maturity

the data stored is encrypted so that in case an unauthorised reader/user was able to gain access to the information, the data would be encrypted and therefore meaningless.

prIvacy In this discussion, I explain the pervasive computing privacy continuum (see figure 2). I begin the discussion at the far left hand side of the model (irrational hysteria) and move to the far right of the model (mature). Watch with any YouTube video on RFID and you will see comments about this technology being the ‘mark of the beast.’ This expression comes of course from the biblical book of revelation. The expression runs to persecution of the so called holy people. Only cash is truly anonymous. With any other more advanced electronic means of exchanging currency, there is a high level of authentication and the trader’s identity is always known. If governments or organisations were to begin to persecute people on the basis of religious belief for example, it would be very easy to make a false entry on an individual’s credit history or to freeze all funds in a back account or even to prevent that individual from leaving the country. Electronic transfer of funds and consumer credit history are already well embedded into the fabric of western society and it is these technologies, more than anything, that represent a loss of anonymity, to be truly free from being identified. RFID is, of course, one technology that facilitates electronic transaction processing, however, to truly believe that it is the mark of the beast is inaccurate and a dramatisation. Despite the hysteria that surrounds RFID and other pervasive technologies, this is not nearly as large a problem as simple ignorance. Only a select few of the population understand, for example, the data that is held in an RFID access key card and how this relates to an individual. In the majority of RFID implementations, all the data that is held in an RFID card is an EPC global unique identification number that can then be matched to a record in a database in a centralised secure location that can then give further information about the user. Misconceptions that are spurred by fictional representations of the future in the movies (i.e., Minority Report) are very often not based on fact and therefore, not accurate. Those that are ambivalent regard pervasive technologies as part of the context or environment. For example, they regard RFID as the new barcode technology and have a very narrow understanding of the application of the technology. That is, that RFID tags will replace barcodes on every product and will allow fast checkout. RFID readers are related to barcode scanners and whether a hospital wristband has a barcode or an RFID tag embedded, there is no real difference. As technologies are released and new applications of new technologies are shown to consumers, there are occasional problems. For example, American Express had the local encryption of data stored in an RFID chip on the actual card cracked by BoingBoing TV and reported all over the Internet. The publicity has been so high that no credit card company will make the same mistake ever again, that is for sure. Card companies will know that more secure private key encryption is required.

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Mature pervasive technology will protect the consumer’s privacy and will assist people. At the moment, the US government has approved human RFID tagging only for special services staff such as policeman and fireman with the purpose being to identify a cadaver. However, think of the recent tsunami crisis in Indonesia where many people were killed. Loved ones endured the agonising wait to find out where the remains of their loves ones were so that they could continue on with their own process of grieving. RFID tags would provide instant identification of people and alleviate many difficulties in cadaver identification. On a more positive note, pervasive technologies are making lasting changes to the way that people are able to live in their own homes. My own work in assisted living devices that use the Goal Management Training approach to help traumatic brain injury patients recover is one of many examples. Some technologies simply provide easier devices to measure changing body states (blood pressure and blood sugar levels for example) by the patient at home and to provide the carer with more up to date information. Other devices provide a summary of complex medical information to predict whether this will be a good day or a bad day and allow the patient to plan accordingly. These devices can be simple as providing a voice recording of the colour of items of clothing on a personal digital assistant for blind people through to complex CCTV and sensor technology to tell whether the user has fallen in their own home and raise the alarm accordingly. Pervasive technologies will make our world better by making it safer, providing users with more real-time information and making life easier. As with all technology, pervasive technologies will follow the differences between intended behaviour and actual behaviour are evident. Fishbein & Ajzen (1975) first wrote about this phenomenon. Here is a practical example to demonstrate this point. Large department stores that have already implemented RFID tags on products heeded customers’ concerns about stores marketing products to them based on previous purchases. This be facilitated when a user purchases an item tagged with RFID and later has that item on their person upon entering another store, which could then allow the store to identify the tagged items and market to the consumer based on that information. The department stores addressed this concern by installing kill stations beyond the checkout area inviting customers to kill their tags after purchase as the product has reached the end of the supply chain. Anecdotally, evidence suggests that the tag killers are not often used. Air NZ Koru Lounge (frequent flyers) customers have been issued with a RFID tag the size of a small button designed to attach to a mobile phone that can be used to automatically check in. The tag contains a unique identification number to identify the customer. The customer’s details are stored centrally on an enterprise system. Suggesting that the customer details be stored locally on the tag was not the chosen solution. Much more detail than just a customer details record is regularly stored in a personal Blackberry and these are often reported lost at a restaurant. It is more that storing customer details and other sensitive information on an RFID tag that can be accessed by others smells of big brother – someone watching. We find this a problem because humans value freedom. Toddlers strive for it, you work your whole life trying to attain it and when you become elderly you will fight tooth and nail to maintain it. So the question is, is your customer details record more secure on you or in an Enterprise Resource Programme? With the customer details record on you, the customer address details are stored in a small device, such as an RFID tag. The address details are matched with a unique id in the ERP system. Provided the customer address information is encrypted, there is no danger of someone skimming the information from your back pocket in the street. Without the unique encryption key, information will be unreadable. A unique ID is difficult to store incorrectly because the number can include a digital check sum. The

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Figure 3. Company A

Customer Address

Company B

Unique ID

Customer Address

Company C

Customer Address

Company A

Unique ID

Company B

Customer Address

Unique ID

Company C

Unique ID

customer has the ability to update the information immediately and there is no need to change multiple instances of the address. Companies must notify the customer of access to the customer address details. Compare this with customer details stored in a company ERP where the unique identification number is the only information stored on the device that the customer has. The unique identification number is associated with the address record in each instance of the customer address each time it is stored. Control of storage of the address is outside the control of the customer and may be stored incorrectly. Also, the organisation accesses the address details when they need to and the customer does not know when their details are accessed. Because there are multiple instances of the customer address, there is the potential that address details can become out of date. Overall, if customers were worried about hackers skimming their personal details stored on electronic devices on their person such as on RFID tags being accessed without their knowledge, then they could always get a foil lined wallet or tote. In fact, as damage control for the recent credit card company that did not encrypt the personal customer information stored on the card well enough, they would manufacture a foil tote with suitable branding. It would be interesting to see how many customers would actually use this, however; it is the gesture to address the perception.

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Professor Andrew Monk of the Centre for Usable Home Technology, University of York in the United Kingdom is linked into the view of “technology to connect you” as opposed to “technology to watch over you.” Professor Monk has been working on the design of conceptual digital jewellery that aims to facilitate communication in extended families through a virtual presence. The Centre for Usable Home Technology also does some fascinating development that engenders pervasive systems. For example, one project was to develop a digital sign to help elderly people immediately see which stove hotplate they had turned on because even with diagrams and led lights on the diagram by the light, the project found that elderly people who find themselves in a strange new place and confronted with many new challenges outside their comfort zone can genuinely become very confused about which knob corresponds to which hotplate and mistakes can lead to kitchen and even house fires. For those that think that the data is safer in the enterprise system, consider the following sobering statistics. The Australian Office of the privacy commissioner reports that in December 2003, a USB stick containing details of over 6,000 prisoners was lost by a health agency in a UK prison. Details of almost 900 customers, including accounts, phone numbers and addresses copied on a USB stick were lost by a Bank of Ireland employee in November 2008. The information was not encrypted. A recent UK survey carried out by a data security firm found an estimated 9,000 USB sticks have been left in people’s pockets when they have their clothes dry cleaned. See www.privacy.gov.au

socIal Issues In our fast paced pervasive environment, social isolation can be a problem, particularly for older family members who live apart from their adult children. Often they only want to know that their children are home at night for example, but they don’t want to bother the children to find out because it seems that they are checking up on them. The adult children have children and jobs of their own and are too busy to remember to call each time they arrive home in the evening. However, researchers at IBM have suggested the concept of a special lamp in the home of the elderly parent which simply comes on when there is someone home and stays off when no one is home.

desIgn We are already seeing some advances in appliance design toward a more ubiquitous environment. For example, dryers can sense when the clothes are dry, washers can sense when they are off balance or overfull of water and fridges can sense when the door has been left open for too long and beep. However, these features are currently only available on high end models and basic entry level appliances still do not have these capabilities. Thinking past fridges and stoves that can take stock and cook, designers are also working on furniture that is intelligent. Take, for example, a concept visualisation of a graduation project at the Design Academy Eindhoven, entitled “An interactive seat which follows the user at the library” (see http:// www.youtube.com/watch?v=2Dgaz6NIUFk). The seats are intelligent enough to follow the user once checked out using a library card and will also return to a ‘seat rank’ once the library patron walks over a line on the floor which signals exiting the library area. The final visualisation shows the seats assembled in lecture hall style ready for a presentation.

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consuMer orIented consIderatIons Most interaction with consumers currently requires consumers to consent to information being collected about them and the best way to do this is to encourage an ‘opt-in’ policy and provide clear guidelines about how to ‘opt-out’. Take for example, new digital data collection laws and codes of ethics. However, in an environment where ambient information is being collected and processed all around them, how do consumers consent to that information being collected about them and how can they ‘opt-out’ of such systems when they are pervasive? There is a difference between spaces. Employees are potentially more at risk when employers use ubiquitous technologies to track information. Tracking of objects is fairly well accepted. Take for example the Aeroscout systems (http://www.aeroscout.com/), which have been used extensively to track high cost hospital assets. The system can track assets in real-time and can provide alerts when too many assets are in one room, for example, or when assets leave a defined area. However, take for example the case of Eastpac, the New Zealand Kiwi Fruit coolstore organisation who installed real-time tracking on every forklift in the coolstore (see http://www.logisticsmagazine.com. au/Article/Kiwi-Fruit-packer-implements-inventory-positioning/173594.aspx). Managers can access a graphical interface showing the layout of the entire coolstore with real-time representation and identity of every forklift. If you have encountered forklift drivers, they rarely alight from their vehicles for their eight hour shift with the forklift wheels becoming their defacto legs. Therefore, by tracking forklifts, Eastpac are essentially tracking forklift drivers in real-time. Eastpac produced an amazing return on investment through not having to pay $.25 million loading penalties and gained efficiency through the real-time location of every pallet of fruit in the coolstore as well as the ability to know about missing pallets of fruit before they are needed and to optimise packing and stacking of the coolstores according to picking orders. However, employee acceptance was slow with forklift drivers initially intentionally disabling their units, ‘forgetting’ to turn them on and not replacing and recharging flat batteries. However, what emerges from this experience are also stories about how the employees were protected by the system in instances where they were on a three minute cigarette break which was confirmed by management who initially assumed that they had been on their cigarette break for 30 minutes and also freedom for blame from damages that occur overnight and for which the culprit might not own up to, thus placing all workers on that shift under a cloud of suspicion. It is argued that employees can choose whether to work in the spaces. They should be informed and they should be able to leave (although this depends on the mobility of the job market and the skills of the individual worker). Public spaces are increasingly being monitored with CCTV. New advances in CCTV technology have been able to provide a blurring effect for all people in the footage so that people with public or low level access have an automatically censored view of the footage where they can recognise a shape as being a person, but the features of the person are blurred. Higher security access allows the uncensored images to be viewed. Spaces that are protected by CCTV should be clearly signed and footage should be kept secure. Monitoring of public spaces does make them more secure.

technIcal orIented consIderatIons Much of the future development around sensors in the network will involve ruggardisation and encapsulation of the sensors. Development is also spurred along by cost and availability.

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Table 3. RFID technology cost vs. ethical obligations Frequency

Read Range

UWB

Military precision

VHF

10m – 100m

UHF

45cm – 75cm read range

HF

5-45cm read range

LF

7-10 cm read range

Cost of purchase

Availability

Ethical Risk

Not available

Extreme

Developers kit approx $US500

Tracient kit available

Some potential for exploitation

Reader < $US100 Tags < 10cents

Phidget kit easily ships & has project book

Low

Table 3 shows some examples of the technology industry either naturally or otherwise showing some ethical consideration for privacy and use of RFID technology. Lower level RFID is freely available at a low cost. However, as the power and reach of the technology increases, so too do the barriers to access which include cost and availability.

Interface desIgn Much of the current human computer interface relies on a visual user interface. Visual interfaces have been fine for most office and productivity work, writing emails, interacting on Facebook and similar. However, once the system begins to move to a more pervasive style, visual interfaces become too cumbersome, requiring the user to direct their attention away from the task and focus on the display device. Visual interfaces are a problem too for mobile devices with small display areas. Mobile music device interface designers are experimenting with much more basic interfaces that allow the user to choose music tracks by interacting with a large graphic. Researchers at Georgia Institute of Technology (http:// sochi.cms.si.umich.edu/?q=content/hci-faculty-candidate-talk-lena-mamykina) in the United States have developed graphical user interfaces that use graphics such as that of an aquarium to communicate complicated medical information. When the user has healthy statistics, there are more fish in the aquarium. On less healthy days, there are fewer fish. This application is a great example of ubiquitous technology being supportive and helpful. The provision of such technologies will mean a better quality of life for those that use it. It is likely that work will channel away from visual output and try to develop voice enables systems and haptic interfaces. This task is being made easier with the widespread use of Bluetooth accessories and some initial work can be seen in the work on the LCD Bluetooth vibrating bracelet (http://www. engadget.com/2009/02/26/lcd-bluetooth-vibrating-bracelet-is-a-watch-short-of-awesome).

analysIs of house vs. car envIronMent Returning to my initial topic of comparing home to car ubiquitous computing environments, I searched out descriptions of leading house designs and car models. I chose Signature homes and a Toyota Levina. Hansmann et al. (2003) in his chapter discussing embedded controls discusses how pervasive technology will be used in home and automotive settings. They give no rationale for choosing the home and the car, however, these are two of the most private and personal spaces in our universe. The home and

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Table 4 Inventory of ubiquitous applications in the Signature Homes House

Technology

Microprocessor fire alarm

X

burglar alarm

X

domestic ventilation systems

X

PAN – cinema/data network BAN

X

Multi-function printer/telephone/fax/scanner

X

MP3s

X

Climate control

X

Microprocessor integrated into everyday object

Omnipresent

Calm

X

X

X

X

X

X

Digital photo frame

X

X

X

Dryer sensing dry needed

X

X

X

Washer sensing off-balance load

X

X

X

Tunstall alarm for frail elderly who live alone

X

Frequency

11

3

X

X

4

7

Total

25

Table 5 Inventory of ubiquitous applications in a late model Toyota Levina

Technology

Microprocessor

Microprocessor integrated into everyday object

Omnipresent

Calm

MP3s

X

Game ports

X

Navigation systems

X

Seating memory

X

X

X

Climate control

X

X

X

Automatic transmission

X

X

X

X

Trip meter/ fuel consumption

X

X

X

X

Hands free phone

X

Key alarm (left in ignition)

X

X

X

X X

Lights on alarm

X

X

X

X

Automatic lighting when you open the door and stays on till you drive off.

X

X

X

X

Parking proximity alarm

X

X

X

X

Radar alert

X

X

X

X

Cruise Control

X

X

X

X

Anti-lock breaking

X

X

X

Airbags

X

X

X

Anti-theft immobiliser

X

X

X

Seat belt on/occupancy/heating

X

X

X

X

X

X

Audible line marking Electronic Windows

X

Frequency

18

Total

11

X

X

13

16 58

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the car are two common environments for ubiquitous computing environments and that is my rationale for choosing them here. For each, I identified a list of ubiquitous computing devices. Based on my research into the definitions for a ubiquitous computing environment, I adopted four criteria; the presence of a microprocessor, whether the microprocessor was integrated into an everyday object, whether the application appeared omnipresent and whether it fit with the calm computing aspect of computing blending into the background. The result of my rough analysis is contained in table 1 for the home environment and table 2 for the car environment. Overall, I was able to identify almost twice the ubiquitous computing applications for the car environment as compared to the home environment. Almost all of the applications involved the embedding of a microprocessor except the audible line marking for the car. More of the applications identified in the car that were embedded into everyday articles seemed omnipresent and also blended into the background. Remember that I restricted my list to ubiquitous computing applications that already existed in either the car or home environment respectively. Other urban ubiquitous technologies that are not yet integrated into the home but do exist in other environments include: • • • • • •

Smart, self cleaning loos Bathroom tap sensors Hand dryer sensors Bin lid sensors Automatic sliding/opening doors Electronic drape drawing

Many of these urban applications are driven by a need for hygiene. Particularly in the current climate of easy and incredibly fast global travel there is a potential for a human plague of gigantic proportions to spread around the world. Current examples of SARS, avian flu and swine flu are all examples. One key way to fight the spread of disease is to minimise contact with communal artefacts such as bathroom tags, door handles and bin lids. Bathroom tap sensors allow users to use the facilities without touching the taps. An interesting additional concept is that of cleaning registries for public facilities. That is, where the facility meets a certain quality of cleanliness standard by being checked every certain number of hours. These are notorious for not being updated correctly. However, consider the notion of a ubiquitous bathroom cleaning register that is updated by the presence of an employee badge and maybe a cleaning cart. This information is very difficult to fabricate while also being very easy to keep current and can be very crucial information in areas highly populated by humans. So, what is driving the development of ubiquitous technology in cars and why is the development so far ahead of similar development in homes? First, let us consider the life of each environment. The overall life of a car (10-20 years) is much shorter than a house life, which might be anywhere between 50 and 100 years and potentially longer depending on construction materials and location. However, the average household appliance life is shorter, possibly 5-10 years. And houses very rarely remain in their original condition for their life and would be remodelled every 10-20 years, particularly around the kitchen and bathroom area. Therefore, the life of each environment does not seem to be much different for either environment. Next, let us consider the potential danger of the environment. The general perception is that the car environment is more dangerous than the house environment. However, statistics do not support this perception. The total number of road deaths in New Zealand over the last 12 months is 371 (number includes pedestrians, cyclists and motorcyclists). It is estimated that 500 people will die in New Zealand

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during 2009 as a results of an injury sustained at home http://www.homesafety.co.nz/didyouknowpresentation/ 65,000 NZers will be injured in their own home each year. (http://www.homesafety.co.nz/ Article.aspx?ArticleId=18 ACC 2008) 11,667 injuries occurred in New Zealand during 2007 (http://www. transport.govt.nz/annual-statistics-2007/ ACC2007). Therefore, statistically, people are injured in and around the home than they are in motor vehicles. Therefore, the home environment is more dangerous. However, both environments are proven to be dangerous, suggesting that the amount of danger associated with the environment is not driving the faster development of ubiquitous computing devices. Next, let us consider consumer convenience. This afternoon I watched as my husband got in our 10 year old Toyota and then got out to close the rear door correctly. A warning light on the dash showed that the door was open. Ok, so sure, there are safety issues with a car and one would certainly not want to be hurtling down the highway at 100km per hour and have a door come open as you go around a sweeping bend. Wouldn’t it be great to have your own personal display that could show, on leaving the house, which doors and windows were open? Granted, this is not a life and death issue, however, it is fully achievable with existing technology for not very much money. Keyless entry has been possible for modern cars for the past 10 years. Computer laboratories and tutorial rooms have been ‘keyless’ in some way even from the early 1990’s with combination locks that require the users to punch in a remembered code. Modern day lecture theatres have keyless entry through RFID enabled swipe cards. However, homes still come with a key to the front door. Not that the dwellers don’t want keyless entry – take for example the remote opening garage and front gate. These allow users to open the garage using a remote control. This is still a far cry from central locking in the car environment. Overall, I think that the most telling factor of why ubiquitous devices are more prevalent in the car environment than in the home environment is simply because automobiles are made in factories by robotic production lines. Automobiles benefit from a wide range of technologies including aerodynamic designs, engine performance, conceptual design models and so on. Houses do not benefit from technology in quite the same way. Houses can be manufactured in pieces and installed on the site, however, there are teams of contractors who must install various aspects of the house and whilst houses generally do benefit from technology such as strength testing and innovation in new materials (such as weather boards with more durable surfaces) they don’t benefit from the same level of technological innovation as for an automobile. The follow on from this is that the home environment lags behind the car environment. However, it is highly likely that trends or applications developed in the car environment will begin to apply to the home environment.

trends It’s nice to have future ubiquitous features for the car. Music choice, by collecting volume information when playing MP3s the system could make a decision about how much I like that particular song by the volume that I play it at and then recommend other similar songs based on that information. Aggregated with several hours of listening preferences, such a facility could be very powerful. IPv6, with its extended address spacing, allows for more IP addresses which will enable enough unique addresses to allow electronic appliances other than PCs to be on the Internet. This will allow domestic appliances such as washing machines, fridges, TV box top sets and motor vehicles to have access to the Internet. IPv6 also allows for enhanced routing and classification which will be necessary with so much more traffic on the Internet.

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Contactless payment will likely be a boom area. Contactless payment will like take over from magnet strip reader systems. The advantage of contactless payment is that the payment process will be faster; it is possible for the payment to be executed without the user removing the associated object from their wallet or purse. Contactless payment systems have already been implemented in high congestion public transport systems such at the Hong Kong International airport. This will be important to speed up checkout process, especially in larger stores with many stores already investing in network infrastructure to make electronic eftpos transactions faster and faster processing meaning smaller cues, or probably more likely less check-out operators. These trends will see telecommunications companies take a much more important position in our environment. Service oriented employment opportunities are likely to decrease. Entirely unmanned service stations already exist where the customer processes the electronic payment and fills up their petrol tank. Banks now actively encourage customers to use Internet banking and ATMs, thus resulting in fewer bank clerk positions. Some airlines have automated check-in where the customer uses a printed two-dimensional barcode to check-in bags and confirm their booking at the airport. This trend is likely to increase in sales and service areas. For example, fashion stores may implement intelligent mirrors that recommend fashion choices, sizes and colours. Jewellery stores may implement sales assistance systems that allow the customer to virtually try out jewellery still at design concept stages. It is very likely that there will be more work in the short term at least services such complex systems. Home automation is likely to increase. Although I have shown in this chapter that the integration of pervasive equipment is slower in houses when compared with cars, I am sure that homes will begin to have such features as keyless entry and locking alarms that alert the owner to open windows on leaving the house. Houses may even evolve to have the equivalent to power windows and blinds. Powerful X10 technology has been available on the market for many years. X10 technology uses the existing power circuit around the house as a network. However, it may be the emergence of the Personal Area Network (PAN) which enables more pervasive technologies in the home because houses more than automobiles are shared spaces and with shared spaces comes complexity and a need for some generality. This perhaps makes pervasive systems within the home much more complex. Perhaps PAN will enable some customisation of shared spaces within the home according to the PAN present. Automatic identification is also likely to increase. RFID tags in some form or another will eventually replace or be incorporated with most barcodes. Every product will be identified with an RFID enabled identification method. Every appliance, vehicle and device will be identified by a unique Internet address. People too will automatically identifiable through RFID tag identification. Mobile phone use is likely to increase. Mobile phone ownership is in reach of many with further price barriers likely to fall. Mobile phones are likely to replace residential phones and could also replace all office phones. Mobile phones will most likely become enabled by voice over IP (VOIP) thus removing the need for cell phone networks. In addition, the mobile phone has been integrated with so many other personal features such as games, music, television and organisers. Users can use their mobile phones to take pictures, set alarms, tell the time and organise their schedule. In addition, second level applications are beginning to become reality such as extended packaging, taking of customer surveys, health monitoring systems that take information from other devices (example heart rate) and relay it to the user via the mobile phone. Even gym exercise plans that use cycle and weight machines and record this information in a history to create motivation and a record of improvement have been proposed. Personalisation is also likely to increase, whether the devices are incorporated into wearable fabrics – such as the vests used by sports athletes to monitor performance or maybe the devices are an extension of the personal mobile phone or are part of personalised medical equipment. As the population of the world increases, it seems that the ability to treat people as individuals also increases. Such a high level

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of personalisation can also mean a high level of personal safety. For example, school children often make their way to and from school unaccompanied. However, they are also electronically protected to check their safe arrival and departure. Globalisation is likely to increase further still. At the desktop computing level, it is becoming easier to video conference. The introduction of applications such as Skype and GoToMeeting has made it possible to conduct virtual group meetings and collaborations without needing highly costly and fixed video conferencing equipment. Skype has already moved into the mobile phone market and it is likely that others will follow. This means that collaborative teams of researchers based around the world can meet more often and work together more interactively.

the Way forWard Wireless networks such as BlueTooth and Zigbee are the fabric of the future that will allow society to weave a rich tapestry of wireless sensors and collections of ambient data and information. As you will be well aware, wireless technology is weakened by many common building materials such as steel and concrete. Therefore, in addition to providing sandboxes for computer science technical development, business development, healthcare and personal development, there is an immense need for sandboxes for architects to be able to play with and understand the technology and its limitations. On the forefront of development, new buildings and designs need to take into consideration the communication needs and develop approaches to building construction that can facilitate pervasive communication. For example http://www.youtube.com/watch?v=dGl9T4fxeoM shows an example of using coloured cards to control lighting (in this case a flight of stairs) and the sounds in a building. The user can place and remove a number of differently coloured cards onto a white table and this action causes the lighting of an internal stair well to change. The internal workings involve RFID tags and a reader as well as a microprocessor and various coloured lights installed in the lighting for the stairwell. This application has pure ‘toy’ status at the moment and you can see how such a demonstrator or sandbox has the potential to stimulate architects to think about wireless communication technology friendly building architectures. However, the legacy of many buildings will remain with us for many decades to come and therefore, designers for architecture and computer science will need to collaborate on innovative ways to overcome existing wireless telecommunication unfriendly situations. To return to the original question about why ubiquitous technologies have developed quicker in cars than houses, I think that this question has become much more symbolic of a much larger issue. If you take the houses to represent buildings and not make distinctions between private and public dwelling spaces, it is important to begin to influence the development of building structures now to intervene in a legacy of telecommunications unfriendly buildings. The forefront of building development that is telecommunications friendly seems to be the apartment complex, especially where there is a lot of control asserted by the developer as is the case in retirement complexes and villages. Many such complexes have instigated fully digital telecommunications systems where telephone access is enabled through the Internet (VOIP). Developer led retirement complexes are a little more like the major car manufacturers when you consider that retirement complexes are a little more technologically advanced to cater for their elderly residents more. My overall feeling is that ubiquitous development is encouraged by highly technologically sophisticated environments. That is why we see the motor vehicle advancing so quickly into the ubiquitous realm. Other transport areas are probably following, such as bus, rail and commuter ferry. To what extent, I am not qualified to comment. Similarly, medical establishments appear to be more interested in techno-

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logical solutions, of which retirement home complexes are part. As this development is accepted into mainstream use (i.e., it becomes part of the ‘background’) it also will extend to less technologically developed areas. In this way, so called toy applications of technological developments are very important because they challenge conventional understanding and also provide a path for more mainstream development of ubiquitous technologies. So, yes, I hope that we will see warning lights on the dash of houses that show that the windows are open, or better yet, such intelligence that my house knows when I have left and shuts all the windows for me.

acknoWledgeMents I have drawn on many of my personal professional networks and experiences in writing this chapter. Many of my personal contacts are mentioned in this chapter and for sharing your ideas with me, I thank you. I hope that I have similarly inspired you.

references Anderson, M. (2009, May). Update: RFID chips gain computing skills. IEEE Spectrum. Ayoade J.. & Symonds J. (2009). RFID for Identification of Stolen/Lost Items. In J. Symonds, J. Ayoade & D. Parry (Eds.), Auto-identification and ubiquitous computing applications. Hershey, PA: Information Science Reference. Bieliková, M., & Krajcovic, T. (2001, October). Ambient intelligence within a home environment. ERCIM News, 47. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley. Hansmann U., Merk L., Nicklous M.S., & Stober T. (2003). Pervasive Computing (2nd ed.). New York: Springer. Hevner, A.R., March, S.T., Park, J., & Ram, S. (2004). Design science in information systems research. Management Information Systems Quarterly. Venkatesh, V, & Davis, F.D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204. Junglas, I., & Watson, R. (2003). U-commerce: A conceptual extension of e- commerce and m-commerce. ICIS 2003 Proceedings. Nielsen, J. (1992). The usability engineering life cycle. Computer, 25(3), 12-22. Ravindranath, L., Padmanabhan, V.N., & Agrawa, P. (2008). SixthSense: RFID-based enterprise intelligence. Paper presented at MobiSys’08 June 17-20, Breckenridge, Colorado, USA. Watson, R. T., Pitt, L.F., Berthon, P., & Zinkhan, G.M. (2002). U-commerce: expanding the universe of marketing. Journal of the Academy of Marketing Science. 30(4), 329-343.

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Weiser, M. (1991). The computer for the 21st century. Retrieved from http://www.ubiq.com/hypertext/ weiser/SciAmDraft3.html Weiser, M. (1996). Ubiquitous computing. Zelkha, E., & Epstein, B. (1998). From devices to “Ambient Intelligence.” Paper presented at the Digital Living Room Conference, June 1998.

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About the Editor

Judith Symonds is a senior lecturer at AUT University (Auckland, New Zealand). Judith serves as Editor-in-Chief of the International Journal of Advanced Pervasive and Ubiquitous Computing. Judith holds a PhD in rural systems management from the University of Queensland (Australia, 2005). Judith has published in international refereed journals, book chapters, and conferences, including the Australian Journal of Information Systems and the Journal of Cases on Information Technology. She currently serves on editorial boards for the Journal of Electronic Commerce in Organizations and the International Journal of E-Business Research. Her current research interests include data management in pervasive and ubiquitous computing environments.

Section I

Fundamental Concepts and Theories This section serves as the foundation for this exhaustive reference source by addressing crucial theories essential to the understanding of ubiquitous and pervasive computing. Chapters found within this section provide a framework in which to position ubiquitous and pervasive tools and technologies within the field of information science and technology. Individual contributions provide overviews of ubiquitous grids, ambient intelligence, ubiquitous networking, and radio frequency identification (RFID). Within this introductory section, the reader can learn and choose from a compendium of expert research on the elemental theories underscoring the research and application of ubiquitous and pervasive computing.

1

Chapter 1.1

Introduction to Ubiquitous Computing Max Mühlhäuser Technische Universität Darmstadt, Germany Iryna Gurevych Technische Universität Darmstadt, Germany

a brIef hIstory of ubIquItous coMputIng Mark Weiser The term ubiquitous computing was coined and introduced by the late Mark Weiser (1952-1999). He worked at the Xerox Palo Alto Research Center (PARC, now an independent organization). PARC was more or less the birthplace of many developments that marked the PC era, such as the mouse, windows-based user interfaces, and the desktop metaphor (note that Xerox STAR preceded the Apple Lisa, which again preceded Microsoft Windows), laser printers, many concepts of computer supported cooperative work (CSCW) and media spaces, and much more. This success is contributed (among other reasons) to the fact that PARC managed to integrate technology research and humanities research (computer science and “human factors” in particular) in a

truly interdisciplinary way. This is important to bear in mind since a considerable number of publications argue that the difference between UC and Ambient Intelligence was the more technology/networks-centered focus of the former and the more interdisciplinary nature of the latter that considered human and societal factors. We do not agree with this argument, in particular due to the nature of the original UC research at PARC—and the fact that quite a number of UC research labs worldwide try to follow the PARC mindset. Indeed, Mark Weiser concentrated so much on user aspects that quite a number of his first prototypes were mere mockups: during corresponding user studies, users had to imagine the technology side of the devices investigated and focus on use cases, ideal form factors and desired features, integration into a pretend intelligent environment, and so forth.

Copyright © 2010, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Introduction to Ubiquitous Computing

Weiser’s Vision of UC Mark Weiser’s ideas were first exposed to a large worldwide audience by way of his famous article The Computer of the 21st Century, published in Scientific American in 1991. A preprint version of this article is publicly available at: http://www. ubiq.com/hypertext/weiser/SciAmDraft3.html. Maybe the most frequently cited quotation from this article reads as follows: “The most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are indistinguishable from it.” This was Mark’s vision for the final step in a development away from “standard PCs”, towards a proliferation and diversification of interconnected computerbased devices. A deeper understanding of Mark Weiser’s visions can be drawn from his position towards three dominant, maybe overhyped trends in computer science at his time: virtual reality, artificial intelligence, and user agents. With a good sense for how to raise public attention, Mark criticized these three trends as leading in the wrong direction and positioned UC as a kind of “opposite trend“. We will follow Mark’s arguments for a short while and take a less dramatic view afterwards.

UC vs. Virtual Reality (VR) According to Mark, VR “brings the world into the computer”, whereas UC “brings the computer into the world”. What he meant was that VR technology is generally based on elaborate models of an existing or imagined (excerpt of the) world. This model contains not only 3D (geometric) aspects but many more static and dynamic descriptions of what is modeled. For instance, digital mockups of cars have been pushed to the point of simulating crash tests based on the car /obstacle geometry, static, and dynamic material characteristics, laws of physics, and so forth. As the sophistication of models grows, more and more aspects of the world are entered into the computer, finally

2

almost everything happens in the virtual space and even the human becomes a peripheral device for the computer, attached via data gloves and head-mounted displays. Mark Weiser criticized mainly the central and peripheral roles of computers and humans, respectively. He proposed to follow the UC vision in order to invert these roles: by abandoning the central role of computers and by embedding them in the environment (in physical objects, in particular), room is made for the human in the center. In this context, he used the term “embodied virtuality” as a synonym for UC. The cartoons in Figure 1 were made by Mark Weiser and provided by courtesy of PARC, the Palo Alto Research Center, Inc.

UC vs. Artificial Intelligence (AI) In essence, Mark Weiser criticized the overly high expectations associated with AI in the 1980’s. In the late 1980’s and early 1990’s, that is, at the time when he developed his UC vision, AI research had to undergo a serious confidence crisis. The term AI had not been associated with a commonly accepted, reasonably realistic definition, so that the association with human intelligence (or the human brain) was destined to lead to disappointments. The AI hype had provided researchers with considerable funds—but only for a while. Mark Weiser proposed to take a different approach towards a higher level of sophistication of computer-based solutions (which had been the goal of AI at large). He considered it a more reasonable objective to concentrate on small subsets of “intelligent behavior” and to dedicate each computer to such a subset. Higher sophistication would be fostered by interconnecting the special-purpose computers and by making them cooperate. This reasoning lead to the term smart, considered more modest than the term intelligent. Sensor technology plays an important role in dedicating computers to a small subset of “understanding the world around us” (a key element of intelligent behavior). By widely deploying and interconnect-

Introduction to Ubiquitous Computing

Figure 1. Mark Weiser’s cartoons about UC vs. virtual reality

ing sensor-based tiny computers, one would be able to integrate environmental data (location, temperature, lighting, movement, etc.) and use this information to produce smart behavior of computers and computerized physical objects.

2.

UC vs. User Agents (UA) In contrast to virtual reality and artificial intelligence, the term user agent is not very prominent in the general public. At the time referred to, UAs were thought as intelligent intermediaries between the user and the computer world, that is, as an approach towards increased ease-of-use or better human-computer interaction. User agents were often compared to the common perception of British butlers who are very discreet and unobtrusive, but always at disposal and extremely knowledgeable about the wishes and habits of their employers. Following this analogy, UAs were installed as autonomous software components between applications and users, inspecting and learning from the user-software application. Mark Weiser challenged five requirements usually derived from this analogy for user agents and proposed UA as a better alternative for the first three; as to the last two, he judged the necessary base technology as immature: 1.

UAs were supposed to give advice to their users based on what they had learned. Mark

3.

4.

5.

Weiser asked, in essence, why they would not do the job themselves—a promise that UC should fulfill; UAs were supposed to obey the user, for example, by applying planning algorithms to basic operations with the aim to fulfill the goals set by a user. In contrast to this approach, UC was intended to behave rather proactively, that is, to propose and even act in advance as opposed to reacting on command; A third widespread requirement suggested that UAs should intercept the user-application interface. UC in contrast should be more radical and take over the interaction or carry out functions on its own—an approach presumed by Mark Weiser to be the only viable one if humans were to be surrounded by hundreds of computers; A basic assumption about UAs was that they would listen to the (interactions of) the user. Mark Weiser considered natural language processing technology and speech recognition technology at his time to be far too immature to promise satisfying results in this respect; UAs should learn the users’ preferences, wishes, and so forth by observation. Again, the necessary (machine learning) technology was judged to be too immature to live up to this promise.

3

Introduction to Ubiquitous Computing

We will resume the VR / AI / UA discussion in the next large section.

Mark Weiser’s Three Key Devices We want to finish this lengthy but still extremely compressed, much simplifying and abstracting treatment of Mark Weiser’s contributions by looking at three devices. These complementary UC devices were prototyped at his lab; investigated in the context of PARC’s typical creative, team-oriented setting, all three were thought as electronic replacements for the common “analog” information appliances. The Xerox “Pad” can be considered to be the prototype and father of present PDA’s, introduced even before Apple’s Newton appeared in 1993. The initial concept was that of an electronic equivalent to “inch-size” information bearers, namely “PostIt Notes”: easy to create and to stick almost everywhere, available in large quantities. As the PDA analogy suggests, the prototypes had a lot more functionality than PostIt Notes—but were also a lot more expensive and cumbersome to handle by design (not only due to short and mid-term technology limitations). The Xerox “Tab” can be considered to be the prototype and father of present Tablet PC’s. The analogy from the traditional world was that of a “foot-size” information bearer, namely a notebook or notepad. One may infer from the rather stalling market penetration of Tablet PC’s that technology is still not ready for mass market “Tabs” today, but one may also expect to find a pen centric, foot size, handheld computer to become very successful any time soon. An interesting facet of the original Tab concept was the idea that Tabs would in the future lay around for free use pretty much as one finds paper notebooks today, for example, as part of the complementary stationery offered to meeting participants. The Xerox “Liveboard” was the prototype of present electronic whiteboards. A PARC spinoff company designed and marketed such boards,

4

and today many companies like Calgary-based SmartTechnologies Inc. still sell such devices. Liveboards represented the “yard-size” information bearers in the family of cooperating devices for cooperating people. In contrast to many devices sold today, Liveboards supported multi-user input pretty early on. The developments and studies conducted at Mark Weiser’s lab emphasized the combination of the three device types for computer supported cooperation, and cooperative knowledge work in particular. While Mark Weiser was a truly outstanding visionary person with respect to predicting the future of hardware, that is, UC nodes (proliferation of worn and embedded networked devices, specialized instead of personal general-purpose computers, numbers by far exceeding the number of human users), two other people were more instrumental in generating awareness for the two remaining big challenges mentioned in the preface of this book, namely integrative cooperation and humane computing; the former of these challenges was emphasized by Kevin Kelly, the latter by Don Norman. A deeper analysis reveals that for the second aspect, humane computing, it is very difficult to argue about the true protagonists. Readers remember that Mark Weiser was actually placing a lot of emphasis on usability, by virtue of his education and mindset and in the context of the human focus of PARC. He also coined the exaggerated term “invisible” for mature technology. On the other hand, Don Norman was not advocating the humane computing challenge in all its facets yet. Nevertheless, we want to highlight him next as maybe the single most important advocate of this challenge.

the book Out of Control by kevin kelly In 1994, K. Kelly published a book entitled Out of Control. The thoughts expressed by Kelly were an excellent complement to Mark Weiser’s

Introduction to Ubiquitous Computing

publications. While the latter emphasized the emergence of networked small “neuron like” (i.e., smart) UC nodes, Kelly emphasized the integrated whole that these neurons should form. His starting argument was the substantiated observation that the complexity of the made, that is, of humanmade systems or technology, approached the complexity of the born, that is, of “nature-made” systems, such as human or biological organisms, human or biological societies (cf. ant colonies), and so forth. This observation led to the obvious requirement to investigate the intrinsic principles and mechanisms of how the born organized, evolved, and so forth. By properly adopting these principles to ‘”the made”, this complexity might be coped with. Research about the organization and evolution of the born should be particularly concerned with questions such as: how do they cope with errors, with change, with control, with goals, and so forth. For instance, beehives were found not to follow a controlling head (the queen bee does not fulfill this function), and it is often very difficult to discern primary from subordinate goals and to find out how goals of the whole are realized as goals of the individuals in a totally decentralized setting. Kevin Kelly summarizes central findings and laws of nature several times with different foci. Therefore, it is not possible to list and discuss these partly conflicting findings here in detail. An incomplete list of perceived central laws “of God” reads as follows: (1) give away control: make individuals autonomous, endow them with responsible behavior as parts of the whole, (2) accept errors, even “build it in” as an essential means for selection and constant adaptation and optimization, (3) distribute control truly, that is, try to live with no central instance at all, (4) promote chunks of different kinds (e.g., hierarchies) for taming complexity, and (5) accept heterogeneity and disequilibrium as sound bases for survival.

the book The Invisible Computer by donald norman Don Norman emphasized the “humane computing” grand challenge described in the preface of this book. World renowned as an expert on usability and user-centered design, he published The Invisible Computer in 1999. He considered the usability problems of PC’s to be intrinsically related to their general-purpose nature and thus perceived the dawning UC era more as a chance than a risk for humane computing. The intrinsic usability problems that he attributed to PCs were rooted in two main anomalies, according to Don Norman: (1) PCs try to be all-purpose and all-user devices—a fact that makes them overly complex, and (2) PC’s are isolated and separated from daily work and life; truly intuitive use—in the context of known daily tasks—is therefore hardly possible. From this analysis, Norman derived various design guidelines, patterns, and methodological implications, which we will summarize again at an extremely coarse level: 1.

2.

3.

4.

He advocated UC nodes using the term “information appliances”: dedicated to a specific task or problem, they can be far simpler and more optimized; He further advocated user-centered development: especially with a specific user group in mind, “information appliances” as described previously can be further tailored to optimally support their users; Norman stated three key axioms, that is, basic goals to be pursued during design and development: simplicity (a drastic contrast to the epidemic “featurism” of PC software), versatility, and pleasurability as an often forgotten yet success critical factor; As a cross-reference to the second big UC challenge (integrative cooperation), he advocated “families of appliances” that can be easily and very flexibly composed into systems.

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Introduction to Ubiquitous Computing

history revised The preceding paragraphs are important to know for a deeper understanding of the mindset and roots of UC. However, about 15 years after the time when the corresponding arguments were exchanged, it is important to review them critically in the light of what has happened since. We will first revise the three “religious disputes” that Mark Weiser conducted against AI, VR, and UAs. To put the bottom line first, the word “versus” should rather be replaced by “and” today, meaning that the scientific disciplines mentioned should be (and have, mostly) reconciled: As to UC and VR, specialized nodes in a global UC network can only contribute to a meaningful holistic purpose if models exist that help to cooperatively process the many specialist purposes of the UC nodes. In other words, we need the computer embedded into the world and the world embedded in the computer. Real Time Enterprises are a good example for very complex models—in this case, of enterprises—for which the large-scale deployment of UC technology provides online connectivity to the computers embedded into the world, that is, specialized nodes (appliances, smart labels, etc.). In this case, the complex models are usually not considered VR models, but they play the same role as VR models in Mark Weiser’s arguments. The progress made in the area of augmented reality is another excellent example of the benefit of reconciliation between UC and VR: in corresponding applications, real-world vision and virtual (graphical) worlds are tightly synchronized and overlaid. As to UC and AI, Mark Weiser had not addressed the issue of how interconnected, smart, that is, “modest”, specialized nodes would be integrated into a sophisticated holistic solution. If the difference between AI and the functionality of a single smart UC node (e.g., temperature sensor) was comparable to the difference between a brain and a few neurons, then how can the equivalent of the transition (evolution) from five pounds of

6

neurons to a well-functioning brain be achieved? Mark Weiser did not have a good answer to that question—such an answer would have “sounded like AI” anyway. Today, there is still not a simple answer yet. The most sophisticated computer science technology is needed in order to meet the integration challenge of how to make a meaningful whole out of the interconnected UC nodes. However, the state of the art has advanced a lot and our understanding for what can be achieved and what not (in short term) has improved. For instance, socionic and bionic approaches have become recognized research areas. A mature set of methods and algorithms is taught in typical “Introduction to AI” classes today and has replaced the ill-defined, fuzzy former understanding of the area. Thus the boundaries between AI and computer science are more blurred than ever and their discussion is left to the public and press. As to UC and UAs, remember that Mark Weiser considered UAs as “too little” in terms of what they attempted (at least too little for the UC world envisioned by him), yet “too much” in terms of what the underlying technology was able to provide. This left doubts about how the even more ambitious goals of UC could be met, namely active (proactive, autonomous, even responsible) rather than reactive (obeying) behavior. In other words, Mark Weiser was right when he advocated active as opposed to reactive behavior, but he had little to offer for getting there. Luckily, the technologies that he had then considered immature (e.g., speech processing, NLP, machine learning) have advanced a lot since. All in all, Mark Weiser’s arguments from 15 years ago (1) provide a deep understanding of the field, (2) should be modified towards a more conciliatory attitude (in particular with respect to AI and VR / complex “world models”), and (3) have become more substantiated in certain respects since technology advancements make some of his more audacious assumptions more realistic (but most visions of his “opponents”, too). In other

Introduction to Ubiquitous Computing

words, Mark Weiser’s visions were and still are marking the research and developments made by the UC community. His concepts and predictions were accurate to a degree that was hardly paralleled by any other visionary person. Restrictions apply as to his overly drastic opposition to VR, AI, and UAs: some of the exaggerated promises of these were repeated by him in the UC context - right when he denounced the over-expectations raised by AI and UAs! VR and AI in particular should be reconciled with UC. Maybe Weiser underestimated the two grand challenges of the UC era, namely “integrative cooperation” and “humane computing”. Kevin Kelly and Donald Norman emphasized these two challenges, respectively. Looking at the advancements in totally decentralized systems, Kelly’s promises can be evaluated as too extreme today: bionics social science inspired, and autonomic (or autonomous) computing have advanced a lot. However, two restrictions still apply: (1) less decentralized systems still prove to be extremely viable in daily operation—it will be hard for fully decentralized systems to really prove their superiority in practice; (2) system-wide goals must still be planned by some centralized authority and—to a certain extent manually—translated into methods for fully decentralized goal pursuit; evolution-like approaches that would generate optimization rules and their pursuit automatically in a fully decentralized systems are still hardly viable. As a consequence, the present book will not only describe the above-mentioned computing approaches in part “Scalability”, but also other aspects of scalability. As to Don Norman, he was right to advocate simplicity as a primary and key challenge. However, he maybe underestimated the ‘humane computing’ problems associated with the nomadic characteristics and ‘integrative cooperation’ challenge of the UC era. The usability of the integrated whole that we advocate to build out of UC nodes is by far not automatically endowed with easy-to-use user interaction just because the

participating appliances exhibit a high degree of usability. On the other hand, only the integration that is, federation of miniature appliances with large interaction devices (wall displays, room surround sound, etc.) may be able to provide the usability desired for an individual device. As we conclude this section, we should not forget to mention that the UC era was of course not only marked by just three visionary people.

terMs and selected standards While there is a lot of agreement among researchers and practitioners worldwide that the third era of computing is dawning as the era of networked, worn/portable and embedded computers, there is not so much agreement about what to call that era. This fact is something of an obstacle, for instance for wider recognition in politics (the crowd does not scream the same name as one may put it). This situation is aggravated by the fact that partial issues and aspects of Ubiquitous Computing are also suffering from buzzword inflation. With this background in mind, one may understand why we list a considerable number of these buzzwords below and provide a short explanation, rather than swapping this issue out into a glossary alone. Knowledge of the following terms is indeed necessary for attaining a decent level of “UC literacy”.

synonyms for ubiquitous Computing First, we want to look at the terms that describe—more or less—the third era of computing as introduced: •

Post-PC era: The root of this term is obvious, it describes ‘the era that comes after the second, that is, the PC era. We suggest avoiding this term since it points at what it

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Introduction to Ubiquitous Computing

•

•

•

8

is not (PC’s) rather than at what it actually is. Pervasive computing: A distinction between the word ubiquitous and pervasive is difficult if not artificial. One could argue that the term pervasive eludes more to the process of penetration (i.e., to the verb pervade) whereas ubiquitous eludes more to the final state of this process. We suggest that pervasive computing and ubiquitous computing are synonyms, one (pervasive) being slightly more common in industry (its origin has been attributed to IBM), the other one (UC) being slightly more common in academia. Ubiquitous computing: The term may be interpreted as “computers everywhere”. We are using it as the notion for the third era of computing throughout the book and prefer it, among others, because we try to fight buzzword mania and dislike the invention of additional terms for a named concept. We therefore propose to stick to the first (reasonable) term invented and somewhat broadly accepted; since Mark Weiser is the first visionary person who sketched essential characteristics of the dawning era and since he invented the term UC, the question of what is the oldest well-known term should not be questionable. Ambient intelligence: This term was invented in particular in the context of the European Union’s research framework programs (5, 6, 7). As a positive argument, one may say that the two words reflect the grand challenges of UC as stated in this book: ambient may be associated with the challenge of humane computing, making UC systems an integral part of our daily life. Intelligence may be interpreted as the challenge of integrative cooperation of the whole that consists of myriads of interconnected UC nodes. On the downside, one should remember that Mark Weiser had intentionally avoided the term

•

•

•

•

“intelligence” due to the over-expectations that AI had raised. We suggest avoiding this term, too, because it is still burdened with these over-expectations and because it is still ill defined. Disappearing / invisible / calm computing: All three terms are less common than UC and pervasive computing. Their roots have been discussed in the historical context above. Obviously, disappearing describes again a process while “invisible” describes a final state. “Calm” emphasizes hearing as opposed to vision like the other two. In any case, the terms “invisible” and “disappearing” are not very well chosen (despite our tribute to Don Norman) since computers and interfaces that have totally disappeared cannot be commanded or controlled by humans any more. Since we doubt that 100% satisfactory service to the user can be paid at all without leaving the customer, that is the user, the option to explicitly influence the service behavior, we consider the term misleading. We favor again Mark Weiser’s notion of computers that are so well interwoven with the fabric of our lives that we hardly notice them. Mixed-mode systems: This is a term used to describe the heterogeneity of UC nodes, in contrast to the rather resource rich, general purpose PC’s of the last era. This term is even less common, but pops up every now and then like those previously discussed, and should not be used to describe UC as a whole since it emphasizes a particular aspect. Tangible bits: This term has found some currency in the Netherlands and Japan, but remained rather uncommon in general. It refers mainly to the fact that networked computers are becoming part of the physical world. Real time enterprise: This term has been explained in the preface of the book and is not

Introduction to Ubiquitous Computing

thought as a synonym for UC, but rather as a very important and cutting-edge application domain that may drive down the learning curve, that is, prices of UC hardware and solutions. It was mentioned in the preface that some authors argued in favor of one or the other of the UC synonyms, saying that their choice was more farreaching in time (the other ones being intermediate steps) or space (the other ones only comprising a subset of the relevant issues). However, we cannot follow these arguments, mainly because research labs and projects around the world work on the same subjects, some more advanced or holistic, some less ambitious or more specialized, carrying the names UC, pervasive computing, and ambient intelligence rather randomly.

towards a taxonomy of uc nodes Throughout this book, UC nodes will be categorized according to different aspects. In the context of reference architectures further below, we will emphasize the role of UC nodes in a holistic picture. In the present paragraph, we want to try categorizing them as devices. It should be noted that in the preface of the book, we already provided a preliminary, light weight introduction. The difference between carried (worn, portable) and encountered nodes was emphasized and four preliminary categories (wearables, sensors, appliances, and smart labels) were briefly described. It soon became clear that smart labels attached to goods must be distinguished again from those attached to humans, although the base technology may be the same. In a second, more serious attempt to categorize UC nodes as device categories, we propose the following distinction (see Figure 2): 1.

Devices attached to humans a. Devices carried: Here we further distinguish three subcategories: (1) mobile

2.

devices, synonymous with portable devices, contain rather general purpose computers and range from laptops via PDA’s to mobile phones and the like, (2) smart badges, that is, smart labels serve for identification, authentication and authorization of humans and possibly further purposes, and (3) body sensors of all kinds play an increasingly important role in particular in the fitness and health context; b. Devices worn: These wearables range from truly sophisticated, computeraugmented cloths and accessories to prototypes that are built from standard components (PDA in a holster with headset, etc.). A further categorization is not attempted since the spectrum is rather blurred; c. Devices implanted: while there is a lot of hype about implanted RFID tags and networked health implants, the many issues (e.g., health, privacy, or dependability) around the necessary device-environment communication have not permitted this category to become widespread. Devices encountered a. Smart items denote computer-augmented physical objects. The terms “smart object” and “smart product” are used with subtle differences depending on the context to denote more sophisticated variants of smart items, such as smart items that proactively communicate with the users. We suggest treating smart items as the most general term and to distinguish the following subcategories: (1) smart tags as the least sophisticated variant: they can be considered to be mimicry for embedded computers: by attaching a smart tag to a physical object, a physically remote computer (often

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Introduction to Ubiquitous Computing

Figure 2. Taxonomy of UC devices

b.

in proximity, though) can take over some of the functionality that would be embedded otherwise. This approach opens the door for turning even the cheapest products into UC nodes. The term “smart label” is sometimes used synonymously; sometimes it is used as the comprehensive term for smart tags and smart badges (attached to humans, see earlier discussion). We suggest sticking to the term smart tag for the smart item sub-category described here; (2) networked sensor nodes, and (3) networked appliances denote the other subcategories of smart items. They were already introduced in the preface of this book. Smart environments denote the surroundings of smart items, that is, the additional communication and compute power installed in order to turn an assembly of smart items into a local, meaningful whole.

The reader must be aware that all terms arranged in the taxonomy are not settled yet for a common understanding. For instance, one might argue whether a sensor network that computes context information for networked appliances and users should be considered a set of smart items

10

(as we defined it) or a part of the smart environment. Nevertheless, we find it useful to associate a well-defined meaning with these terms and to apply it throughout the book (see Figure 2). In addition, it should be noted that smart environments (with integrated smart items) constitute a particularly important research area—maybe because they permit researchers and project leaders to implement self-contained “little UC worlds” without a need for multiparty agreements about interoperability standards. In particular, “smart homes” were among the first subjects of investigation in the young history of UC. Prestigious projects in the smart home area were and are conducted by industry (Microsoft eHome, Philips AmbientIntelligence initiative, etc.) and academia (GeorgiaTech AwareHome, MIT House, etc.). HP made an early attempt to overcome the isolation of such incompatible islands by emphasizing standard middleware in the Cooltown project). Quite a number of projects about smart homes terminated without exciting results, not to the least due to insufficient business impact (note our argument in favor of Real Time Enterprises as a more promising subject). More recently, smart homes projects have focused on issues considered to be particularly promising, as was discussed in the preface to this book. Important areas comprise home security, energy conservation, home entertainment, and particu-

Introduction to Ubiquitous Computing

larly assisted living for the aging society—a topic considered particularly interesting in Europe (1 year prolongation of independepnt living saving about half a billion Euros in Germany alone). Renowned large-scale projects were carried out, for example, in Zwijndrecht (Belgium) and Tønsberg (Norway) in this respect.

•

a few More relevant terms A few more UC terms—and sometimes, corresponding concepts—are worth mentioning. •

•

•

•

•

Smart dust is a term used for sensor networks if the emphasis is on miniaturization and the concept is based on one-time deployment and zero maintenance. Environment data sensors are often cited as an example, the vision then is to deploy them, for instance, from an aircraft, and let them monitor the environment until they fail. Environmentfriendly degradation is a major issue here, of course. Things that think was the name of an early UC project led by Nicholas Negroponte at the MIT media lab. Other authors have since hijacked the term. Smart paper denotes the vision of a display device that would exhibit characteristics comparable to traditional paper in terms of weight, robustness, readability, and so forth, and loadable with the content of newspapers, journals, books and so forth,. it would help to save paper and revolutionize the press distribution channels and more. Many projects that were not even close to this vision had, and continue to have, the name “smart paper”. Smart wallpaper is a similar term to smart paper in that it extrapolates the above mentioned characteristics to wall-size devices. Smart : virtually every noun has been associated with the attribute smart recently, not always alluding to the

characteristics of UC nodes. For instance, smart materials are supposed to adapt to the context of use, with no IT involved. Most of the time though, smart alludes to a physical object that has been augmented with an embedded computer. The Internet of things is a term favored by the press. It is not considered appropriate as a term for UC as a whole by the authors since it emphasizes the hardware side of UC as opposed to the human side, which was already described as crucial and as a major challenge (cf. humane computing). Most publications that favor this term concentrate on the two standards discussed in the following section.

the epcglobal standard As mentioned at the beginning, we will only sketch two important standards in the UC context. Other standards are too unimportant, too immature, too specific (they might be treated in one of the focused parts of this book), or part of the background knowledge about well-established technology that this book cannot cover. The first standard to mention is EPCglobal and was mentioned in the preface of this book. As mentioned, it is meant to succeed the barcodes that encode the European article number or universal product code on current consumer products. The 96-bit Electronic Product Code EPC is usually stored on RFIDs (a subcategory of smart tags, as we can now say) and can be read: • • •

•

From a greater distance (e.g., 10m) With better reading accuracy With much less effort (e.g., en-passant by a RFID reader gate as opposed to carefully with line-of-sight connection by a barcode scanner) In bulk (RFID readers can read, for example, a hundred tags at once)

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Introduction to Ubiquitous Computing

Since the EPC contains a 36-bit serial number, individual items can be tracked and traced. For instance, theft can be much more easily attributed to criminals, product life cycles can be recorded more accurately, product lots with manufacturing errors can be called back more specifically, etc. On the other hand, the serial number may in principle be used to trace an individual, too, if she carries around an RFID tagged product. This privacy issue has raised many concerns in recent years and amplified the decision of the whole sales and retail industry to focus on tagging their containers, palettes, cases, etc., for a start. So-called item level tagging is only envisioned for highly valuable goods initially; it may enter the mass market when tag prices and system costs have come down and after settling the privacy issues. Figure 3 depicts the functioning of EPC smart tags in an overall IT infrastructure. In step 1, an EPC code is read from a product. In the example, each carton on the palette could contain a number of tagged products. The residual example would then explain the action for just one such tag. Usually prior to reading the tag, the system has already searched and discovered servers capable of ‘resolving’ certain ranges of EPC code. Based on the results of this discovery process, the appropriate ‘resolution node’, called an ONS server, is asked to resolve the EPC code, that Figure 3. RFID / EPC scheme

12

is to translate it into a global Internet address where the relevant product information is actually stored. The product information is encoded in a standardized way, using the so-called product markup language PML, an XML derivate. The second generation of RFID tags introduced in 2006 features improved bulk reading (hundreds of tags simultaneously), size and cost improvements. “Printable” tags have become common: these paper labels with embedded RFID chips can be custom imprinted with custom human-readable information. The chips themselves are not altered in the printer and they come with pre-assigned EPC codes from the manufacturer.

the osgi standard The Open Services Gateway Initiative (OSGi) is an industry driven nonprofit consortium. OSGi standardized a Java virtual machine (JVM). This JVM can be considered a standardized virtual ‘computer’ that runs on any real computer and is capable of executing programs that are transmitted to it, so-called bundles. OSGi standardizes not only the format for bundles, but also the necessary protocols and procedures for authenticating and authorizing senders of bundles, for replacing and updating bundles (remote maintenance), for discovering other bundles, and so forth. OSGi

Introduction to Ubiquitous Computing

bundles are particularly useful for controlling the functionality of networked appliances. Possible use cases include SetTopBoxes, Vehicles (note that car electronics today requires much shorter maintenance cycles than the mechanical parts, especially for software updates!), consumer electronics, and so forth. As to smart homes, the favored concept is that of a residential gateway that is connected to the global Internet and receives updates for smart home appliances via OSGi. The residential gateway may then forward bundle updates and so forth to the relevant appliances if needed. OSGi has a number of deficiencies. For instance, it is not considered to be very resource effective. Nevertheless, it has tremendous impact as a de facto standard for dealing with some of the elementary aspects of coping with global UC systems in a platform and vendor independent way.

reference archItectures for ubIquItous coMputIng The Importance and Role of a reference architecture A sophisticated distributed infrastructure is needed in order to make a myriad of networked UC nodes communicate and cooperate. If interoperability is to take on a worldwide scale, means for agreement among arbitrary participants must be provided. Ideally, the move from isolated proprietary UC solutions to a world of cooperating UC components is driven by so-called reference architectures which establish several levels of agreement: on level one, a common terminology and conceptualization of UC systems is established in order for researchers and practitioners to speak the same language and to work on the same global UC vision. On the second level, a common understanding of the ensemble and components of a typical UC system is established, including the

potential roles of the components. On level three, basic functional principles can then be agreed upon. A fourth level is desirable but beyond the scope of reference architectures, that is concrete standards for intercomponent cooperation. This level is discussed in the introduction to the part Scalability.

Reference Architectures in a More Realistic World In reality, a worldwide common understanding and corresponding standards have to be developed in a struggle for the best solution. Real life has a large impact on what becomes widespread. By “real life” we mean breaking research results, industry practice, experiences gained with proprietary prototypes and realizations, user acceptance, and not least business interests defended by global industrial players. Nevertheless, the exercise of proposing and refining reference architectures—in communication with the stakeholders mentioned—plays a key role in a struggle for globally interoperable solutions. Here reference architectures must be invented and published and then consolidated and reiterated based on feedback by the stakeholders.

Prominent Examples from the Past The ISO reference architecture for open systems interconnection (OSI) was developed in the 1970s as an important step towards global networks. OSI was very successful in that it led to a common terminology and a common understanding of the components of computer networks including their roles. The fourth level aforementioned above: ISO standards for communication protocol, were not nearly as successful as the reference architecture itself. Rather, the Internet protocols TCP and IP took over almost the entire market. Nevertheless, the OSI reference architecture was extremely influential on the computer networking community as a whole and on the Internet in particular.

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Introduction to Ubiquitous Computing

Another ISO reference architecture is ODP (open distributed processing). It emphasizes complex distributed systems and applications. An influential contribution of ODP is its support for different viewpoints of various stakeholders. In particular, ODP emphasized the importance of enterprise modeling for application development. All too often, applications are modeled and built with a technology focus and thus neglect the (dynamically changing) organization they should support. ODP addresses important issues, but came at a time when distributed applications were usually rather simple: ODP was considered overkill.

•

Layered Architectures vs. Component Architectures

Although we focus on the Computer Networks / Distributed Systems aspects of UC in the remainder of this chapter, readers should note that the entire book represents a holistic approach.

Before we introduce concrete reference architectures, it is worth recalling the two complementary flavors: •

14

Layered reference architectures serve as a blueprint for layered software architectures. Both arrange sets of functions into layers that act as virtual machines: only the “what” (provided functionality and how to access it) must be known to users in higher layers, whereas the internal “how” (realization) is hidden and can be independently modified. The layer stack represents the range from higher to lower function sets, where higher means “closer to what users and applications need” and lower means “closer to what hardware provides”. Strict variants preclude higher layer components to access lower layers except for the one immediately below. Recent research has concentrated on approaches for automatic, selective custom configuration of the entire layer stack, according to the needs of applications—this trend is important in the UC world where dedicated, resource-poor UC nodes cannot host fat all-purpose layers.

Component reference architectures take a birds-eye view on the world addressed. They define a number of cooperating components or rather component types, and specify inter-component cooperation at a certain level of detail. Again, a kind of art of right-sizing exists: too few component types do not really help to understand and discern relevant roles and specializations common to the world addressed, too many component types lead to overly complex architectures and problems in matching reference and reality.

Why Component Reference Architectures are Important for UC The OSI reference architecture assumes a network consisting of rather homogeneous nodes, namely general-purpose computers with ‘sufficient’ CPU and memory capacity. Accordingly, a common definition of a computer network reads as follows: A computer network CN is a set of autonomous nodes AN, each of which disposes of CPU(s) and memory, plus a Communication Subsystem CSS capable of exchanging messages between any of the nodes: CN :== {AN} ∪ CSS. In the definition, “all nodes are created equal”. At a closer look, computer networks rely on four mandatory constituents of nodes (ANs): 1. Communication capability: The capacity of exchanging messages with other nodes through the CSS. 2. Address: A unique identifier that can be used to specify the recipient or sender of messages.

Introduction to Ubiquitous Computing

3. Processor: A general purpose CPU. 4. Memory: Means for storing—at least—incoming messages. In a UC world, resource scarcity and the special-purpose nature of many nodes are key issues. A holistic UC approach must scale from servers to sensors and support the consideration of smart labels etc. The definition of a UC node must be different from the one above—the four constituents now read as follows: 1. Communication is mandatory, but may be passive (cf. passive RFID tags) 2. Address is not necessarily a unique identifier; for example, in a sensor network, a random node out of a redundant set with identical address may provide a certain functionality 3. Processor becomes an optional constituent 4. Memory becomes an optional constituent, too With the above modifications, not all nodes are autonomous (ANs) any more.

Proposed UC Component Reference architectures The definition introduces a first possibility for distinguishing nodes as components of an application, that is, from the component architecture point of view. However, it only discerns between existing versus missing fundamental characteristics. More interesting is the aspect of different roles that nodes can play in the network—not application specific roles, but fundamental roles in the set of cooperating resources. Thus UC systems will take on more complex node topologies than what was considered in the eras of simple interprocess communication and client-server computing. In addition, a holistic approach needed for UC systems raises issues such as security, which are

important when trying to find important node types at different levels of granularity. One of the first proposals for a UC component reference architecture was made by the Fraunhofer research institute FOKUS in Berlin. They did not distinguish different node types that would assume different roles, but identified important roles that each UC node may potentially assume. Their concept is coined I-Centric Services and achieved a certain level of influence on the industrial Object Management Group (OMG). In their view, a UC node (usually a software service) should provide standard interfaces for four major issues: 1. Discovery of peers in a spontaneous, configuration-free manner 2. Maintainance, i.e., software update and revision 3. Reservation, that is, pre-allocation of some of the node’s resources as a basis for service guarantees 4. Configuration as a means for customizing the service for a dedicated role Nodes that conform to these interfaces are called super distributed objects (SDO) in this proposal. We will discuss another component architecture in some more detail since it attempts to discern between more specific roles of UC nodes. It was developed in the Telecooperation Group at the Technische Universität Darmstadt and is called Mundo, see Figure 4. Mundo distinguishes five different node types: Me, us, It, We, and they. Me (Minimal Entity): Mundo emphasizes the importance of a distinct personal UC node, that is the device tightly associated with its user: the Me. Every user uses exactly only one Me at any time. The rationale is rooted in the envisioned ubiquity of computer support in everyday life: if every step that one takes is potentially computer supported and controlled, then humans need a high level of trust that the computers “do the right thing”. For instance, users will want to make sure

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Introduction to Ubiquitous Computing

Figure 4. Mundo reference architecture

that their actions are only recorded and disclosed to the degree they consent to or that is legally imposed. As another example, they want to be sure that they only trigger actions which they understand in their legal, financial, and other consequences and that they agree to. To this end, the Mundo researchers propose to conceptualize a single, truly owned UC node type that acts in the user’s stead and controls when, how, and to what extent other UC node types are invited or chartered to participate in actions. Since computer use becomes ubiquitous, such a personally-owned node type must be carried along virtually at all times. This imposes strong requirements with respect to miniaturization, robustness, and the conflicting goals of (a) the impossibility to falsify or duplicate such a node, and (b) the possibility to replace it easily in case of theft or failure. An important research questions is concerned with the minimum functionality of a Me. Me nodes are considered as the representation of their users in the digital world—a digital persona involved in all user activities. It is a small wearable computer with minimal functionality. In order to support interaction with UC environments in a sensible way, the term minimal must be associated with a set of specific requirements regarding size, identity, security, interaction, context awareness, and networking. The design was guided by the principle that the minimal feature set of a system is determined by the worst-case environmental conditions under which the application must run satisfactorily (Satyanarayanan, 2001). This leads to a focus on speech based interac-

16

tion and it is described in detail by Aitenbichler, Kangasharju, and Mühlhäuser (2004). Any Me can augment its capabilities through association with other entities of the Mundo architecture as described next. Us (Ubiquitous aSsociable object): Minimization pressure will not permit feature-rich Mes. Hence, they must be able to connect to other mobile devices or devices embedded into the environment to offer more powerful services to their users, such as large display space. This process is called association and such devices are called ubiquitous associable objects (us). A us is a computing device that extends the user’s personal environment by adding storage, processing capacity, displays, interaction devices, and so forth. During association, the Me sends authentication information to the us, sets up a secure communication link, and personalizes the us to suit the user’s preferences and needs. For privacy reasons, any personalization of a us becomes automatically unavailable if it is out of range of the user’s Me. It (smart ITem): There are also numerous smart items that do not support association that would classify them as us. Vending machines, goods equipped with radio frequency IDs, and landmarks with “what is” functionality are just a few examples. Such devices are called smart items (Its). An It is any digital or real entity that has an identity and can communicate with a us or the Me. Communication may be active or passive. Memory and computation capabilities are optional (cf. the four constituents of a UC node described previously). We (Wireless group Environment): Ad-hoc networking is restricted to an area near to the user of a Me device, as connections with remote services will involve a non ad hoc network infrastructure. The functionality of a wireless group environment is to bring together two or more personal environments consisting of a Me and arbitrary us entities each. It enables cooperation between the devices and also allows for sharing

Introduction to Ubiquitous Computing

and transferring hardware (e.g., us devices) and software or data between We users. they (Telecooperative Hierarchical ovErlaY) stands for the backbone infrastructure as part of the Mundo component architecture. It connects users to the (nonlocal) world, and delivers services and information to the user. The they integrates different physical networks and provides transparent data access to users. Frequently used data may be cached on us devices.

are often called smart spaces or more specifically smart houses, labs, offices, homes etc. Work on these kinds of environments emphasizes the tangible, physical (computer-augmented) objects to be handled. As for smart information spaces, an interesting reference architecture was proposed in the LifeSpaces project in South Australia (Bright & Vernik, 2004). Their architecture incorporates some of the findings from ODSI and distinguishes four layers:

uc layered reference architectures 1. Many actual UC projects are based on a layered architecture. Most of them are just first approaches to software architectures, only a few of them are intended to serve as a crystallization point for the community and future standards. Nevertheless, one of them may turn out to be so successful that a future reference architecture will evolve from it. We will concentrate on a small selection of the few projects that have a general reference model in mind. They concentrate on different challenges or foci, that is their findings will have to be merged if a holistic layered architecture is to be derived. A first focus is the enterprise modeling that ODP already addressed. A reference architecture worth mentioning here is ODSI, the so-called open distributed services infrastructure (Bond, 2001). Although already outdated, ODSI was influential since it fostered the move away from ODP’s more top-down approach to a component-based, that is service based approach that supports the concept of applications being compositions of services. Other reference architectures emphasize Smart Environments. Two facets are important and investigated—still—in different camps even as to the work on reference architectures: smart information spaces and smart physical spaces. By smart information spaces, we mean environments which concentrate on cooperative treatment of ITand data/media centric work (cf. Mark Weiser’s three initial UC devices). Smart physical spaces

2.

3.

4.

Enterprise model: This layer supports rules, processes, and organizational models of roles and services in the enterprise. Coordination and control including interaction support: On this layer, a shared and persistent event space of limited capacity, and an agent-based workspace infrastructure are offered. Enterprise bus: This term refers to a communication layer based on the publish/subscribe paradigm. The service layer: Here, the core functionality is represented by easily composable services. An enterprise bus is offered for services to communicate and cooperate; this bus connects so-called peers which host the services.

As for smart physical spaces, a prominent example is the reference architecture developed by the Gator Tech Smart House project of the University of Florida (see Figure 5). The reference architecture depicted is a more recent version of what was published by Helal, Mann, El-Zabadani, King, Kaddoura, and Jansen (2005) and is included by courtesy of the authors (the commercial version is called Atlas now). For more information, the reader may consult the group’s Web Site at www. icta.ufl.edu or the Atlas Web site at www.pervasa. com. The architecture emphasizes sensors (plus actuators) and networked embedded devices at the lowest layer as the hardware foundation of UC

17

Introduction to Ubiquitous Computing

Figure 5. SmartSpace middleware layered reference architecture

applications. The OSGI standard is exploited for customizing and maintaining these sensors and embedded devices in a dedicated second layer. The third layer contains three large parts which reflect major insights into the nature of the UC world (note that these insights have a large influence on the present book, too): •

•

•

18

The context management layer reflects the importance of context-awareness for UC as a whole, as discussed in the preface of the book; The service layer reflects services (and service-oriented architectures, SOA) as the dominating paradigm for building autonomous software components in a UC setting; The knowledge layer reflects the fact that large-scale service composition cannot rely on standardized interfaces that are distributed prior to software (service) development; rather, service discovery and service interaction must rely on machine readable descriptions of the service semantics available at runtime;

•

Due to the strictly service-oriented concept used, application development boils down to service composition; the top layer offers corresponding tools.

In conclusion, it should have become clear that both a component based and a layered reference architecture, if widely accepted, would be important steps from UC islands towards truly global UC. The reference architectures presented could serve as a basis for better communication among the UC protagonists and for the necessary standards.

references Aitenbichler, E., Kangasharju, J., & Mühlhäuser, M. (2004). Talking assistant headset: A smart digital identity for ubiquitous computing. Advances in pervasive computing (pp. 279-284). Austrian Computer Society. Bond, A. (2001). ODSI: Enterprise service co-ordination. In Proceedings of the 3rd International Symposium on Distributed Objects and Applications DOA‘01 (pp. 156-164). IEEE Press.

Introduction to Ubiquitous Computing

Bright, D., & Vernik, R. (2004). LiveSpaces: An interactive ubiquitous workspace architecture for the enterprise in embedded and ubiquitous computing. Springer (pp. 982-993).

Helal, A.A., Haskell, B., Carter, J.L., Brice, R., Woelk, D., & Rusinkiewicz, M. (1999). Any time, anywhere computing: Mobile computing concepts and technology. Springer.

Helal, S., Mann, W., El-Zabadani, H., King, J., Kaddoura, Y., & Jansen, E. (2005, March). The Gator Tech Smart House: A programmable pervasive space. IEEE Computer, 38(3), 64-74.

Huber, A. J. F. & Huber, J.F. (2002): UMTS and mobile computing. Artech House.

Satyanarayanan, M. (2001). Pervasive computing: Vision and challenges. IEEE Personal Communications (pp. 10-17). IEEE Press.

addItIonal readIng Aarts, E., & Encarnaco J. L. (Eds.). (2006). True visions. The emergence of ambient intelligenc. Berlin, Germany: Springer. Adelstein, F., Gupta, S. K. S. et al. (2004). Fundamentals of mobile and pervasive computing. New York: McGraw-Hill Professional Publishing. Antoniou, G., & van Harmelen, F. (2004). A semantic web primer. Massachusetts: MIT Press. Hansmann, U., Merk, L. et al. (2003). Pervasive computing handbook. The mobile world. Berlin, Germany: Springer. Hedgepeth, W.O. (2006): RFID metrics: Decision making tools for today’s supply chains. University of Alaska, Anchorage, USA

Jurafsky, D., & Martin, J. H. (2000). Speech und language processing. Upper Saddle River, NJ: Prentice Hall. Lu, Y., Staff, L.Y., Zhang, Y., Yang, L.T., & Ning, H. (2008). The Internet of things. Taylor & Francis Group McTear, M. F. (2004). Spoken dialogue technolog. London: Springer. Moreville, P. (2005): Ambient findability. O’Reilly. Riva, G., Vatalaro, F., Davide, F., & Alcañiz, M. (2005): Ambient intelligence. Amsterdam: IOS Press. Sharp, H., Rogers, Y., Preece, J. (2002). Interaction design: Beyond human-computer interaction. J. Wiley & Sons. Stajano, F. (2002). Security for ubiquitous computing. Cambridge: John Wiley & Sons, Ltd.

Weber, W., Rabaey, J. M., & Aarts, E. (Eds.). (2005). Ambient intelligence, Berlin, Germany: Springer.

This work was previously published in Handbook of Research on Ubiquitous Computing Technology for Real Time Enterprises, edited by M. Mühlhäuser and I. Gurevych, pp. 1-20, copyright 2008 by Information Science Reference, formerly known as Idea Group Reference (an imprint of IGI Global).

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20

Chapter 1.2

Ubiquitous Computing History, Development, and Scenarios Jimmy Chong Nanyang Technological University, Singapore Stanley See Nanyang Technological University, Singapore Lily Leng-Hiang Seah Nanyang Technological University, Singapore Sze Ling Koh Nanyang Technological University, Singapore Yin-Leng Theng Nanyang Technological University, Singapore Henry B. L. Duh National University of Singapore, Singapore

abstract

IntroductIon

This chapter gives a brief history of ubiquitous computing, highlights key issues, and assesses ubiquitous computing research and development under the broad categories of design architecture and systems, implementation challenges, and user issues. Using Singapore as a case example, the chapter then concludes with selected scenarios, presenting exciting possibilities in the future ubiquitous landscape.

history and vision of ubiquitous Computing Technology in computing has undergone extensive changes over the years. In the early 1970s, mainframe computers dominated the computing scene based on the principle of one computer serving many people. In the 1980s, mainframe computers gave way to personal computers and notebooks,

Copyright © 2010, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Ubiquitous Computing History, Development, and Scenarios

and, in contrast, the emphasis was one computer to one person. In the 1990s, with increased computing powers available at affordable prices, we are witnessing a new era of personal computing, that is, a phenomenon in which multiple computers are serving one person. Through the ages, technology has dramatically transformed our lives, changing the way we learn, live, work, and play. Technology shrank transistors to such microscopic sizes that they enable computer chips to be found in the things we use daily, even down to a pair of shoes made by Adidas (McCarthy, 2005). Technology also connects computers around the world breaking down geographical boundaries as people are able to “travel” virtually everywhere, collaborate with others online, and be connected with loved ones virtually even though they may be miles away physically. Mark Weiser (1991; 1993a; 1993b), father of “ubiquitous computing” (or “ubicomp” in short), coined the term “ubiquitous” to refer to the trend that humans interact no longer with one computer at a time, but rather with a dynamic set of small networked computers, often invisible and embodied in everyday objects in the environment. Keefe and Zucker (2003) see ubicomp as a technology that enables information to be accessible any time and anywhere and uses sensors to interact with and control the environment without users’ intervention. An example often cited is that of a domestic ubicomp environment in which interconnected lighting and environmental controls incorporate personal biometric monitors interwoven into clothing so that illumination and heating conditions in a room might be modulated according to “needs” of the wearer of such clothing. Other examples of ubiquitous environment include applications in homes, shopping centres, offices, schools, sports hall, vehicles, bikes, and so forth. The principle guiding ubicomp is the creation of technology that brings computing to the background and not the foreground, making technology invisible. Philosophers like Heidegger

(1955) called it “ready-to-hand” while Gadamer (1982) coined it “horizon.” This means that people do not need to continually rationalize one’s use of an ubicomp system, because once having learned about its use sufficiently, one ceases to be aware of it. It is literally visible, effectively invisible in the same way, for example, a skilled carpenter engaged in his work might use a hammer without consciously planning each swing. Hence, ubicomp defines a paradigm shift in which technology becomes invisible, embedded and integrated into our everyday lives, allowing people to interact with devices in the environment more naturally.

current research challenges Research challenges in ubicomp remain interdisciplinary, and this is evident as we trace the development of the Ubicomp Conference Series into its ninth year in 2007. The conference series began as Handheld and Ubiquitous Computing in 1999, focusing on areas relating to the design, implementation, application, and evaluation of ubicomp technologies, a cross-fertilization of a variety of disciplines exploring the frontiers of computing as it moves beyond the desktop and becomes increasingly interwoven into the fabrics of our lives. Over the years, the Ubicomp Conference Series from 1999 – 2006 has grown in participation by region, with papers addressing more diverse application areas, as well as innovative supporting technologies/media (see Table 1). In the following sections, we highlight key issues and assess the current situation of ubicomp research and development under the broad categories of design architecture and systems and implementation issues.

design architecture and systems For the ubicomp vision to work, we need an infrastructure supporting small, inexpensive,

21

Ubiquitous Computing History, Development, and Scenarios

Table 1. Breakdown of participation by region, application areas and technologies ubicomp conference series from 1999-2006 Ubicomp Conf

Region Asia Pacific

Europe

Application Areas U.S. & Canada

Education

Health Care

Tourism

Technologies Gen

Others

Mobile Devices

Internet

Wireless

Several Devices

Others

1999 (53 paper)

4

39

10

1

1

3

40

8

13

3

-

5

32

2000 (18 paper)

2

8

8

-

1

-

14

3

3

1

-

2

12

2001 (30 paper)

1

12

17

2

-

3

23

2

2

3

2

10

13

2002 (29 paper)

2

14*

15*

1

2

2

19

5

1

1

-

5

22

2003 (26 paper)

-

8

18

1

2

1

19

3

2

-

1

7

16

2004 (26 paper)

3

7*

17*

2*

2*

1

17

5

-

-

1

4

21

2005 (22 paper)

2

10*

12*

-

3

-

16

3

4

-

1

1

16

2006 (30 paper)

4*

7

20*

-

4

2

19

5

7

1

1

2

19

Note:* in 2002: 2 papers written by Europe-U.S. authors * in 2004: 1 paper written by Europe-U.S. authors; 1 paper can be applied both in education and health care * in 2005: 2 papers written by Europe-U.S. authors * in 2006: 1 paper written by Asia-U.S. authors

robust networked processing devices. Current contemporary devices giving some support to this vision include mobile phones, digital audio players, radio-frequency identification tags and interactive whiteboards. For a fully robust ubicomp implementation, we also require a better understanding of the yet-to-emerge “natural” or intuitive interaction paradigms. Challenges facing design architecture and systems also include issues relating to the wireless network, power component, and standards for service discovery. In the ubicomp world, anyone can interact with thousands of wirelessly connected devices, implying implicit mobility. Hence, mobility and density of data transferred require a robust network infrastructure in place. Such networks should have the capacity to transmit and receive wireless data at ultrahigh speed virtually anywhere and everywhere.

22

Different standards are currently adopted by different countries, for example, the U.S. standards include analog and digital services; GSM, the European standard, is meant for wide area cellular service; Japan uses CDMA, and so forth, and hence pose problems in interoperability. In order to build a better wireless network environment, some countries are working towards adopting the WiMAX wireless broadband technology in cooperation with telecommunications operators to create wireless broadband cities. Examples include Mobile-Taiwan project (Mobile Taiwan Initiative, 2004) and Singapore SG@Wireless project (Wireless@SG, 2006). Increased use of wireless networks and mobile devices has also resulted in increasing need to manage and administer the interconnection of networked devices with less complexity. Wireless and mobile infrastructure will play a major role in achieving the ubicomp vision; hence, more research should be done to resolve current issues.

Ubiquitous Computing History, Development, and Scenarios

Design and Implementation challenges The ubicomp paradigm presents a novel interpretation of the post-desktop era, and these interfaces thoroughly integrated into everyday objects and activities have to take on different forms. This means that users “using” ubicomp devices engage themselves in many computational devices and systems simultaneously, and may not necessarily even be aware that they are doing so when performing these ordinary activities. Hence, models of contemporary human-computer interaction describing command-line, menu-driven, or GUI-based interfaces may seem inadequate. The challenges facing designers are in making access easy for users to retrieve information on the Internet through either desktops or handheld devices. We discuss some of these challenges in design and implementation: •

•

•

Smaller screen display. Designers need to work within constraints of smaller screen sizes when displaying information (Want & Pering, 2005). Scalable interfaces are also explored as applications extend to desktops, PDAs, and even phone interfaces (Abowd, 1999). Location-based and context-sensitive data. Many ubicomp applications “push” information based on the location of users and display information implicitly to users on a mobile device (Rogers, Price, Randell, Fraser, & Weal, 2005). Hence, designing ubicomp systems also requires designers to consider context awareness. Information needs to be personalized according to user’s location, time, mood, and history (Abowd, 1999). Cultural differences. Users are diverse and they can come from all over the world. We need to have in place some degree of

standardization to prevent diverse cultural conflicts (Rosson & Carroll, 2002). • Privacy. With widespread use of wireless broadband, we have to be vigilant in protecting our personal information and our personal network access. Users should be educated that tapping into other people’s wireless network is unethical and that detailed tracking of individuals accessing illegally is possible (IDA, 2005b). Yamada (2003) highlighted privacy management considerations asking three fundamental questions: (i) “where” to store personal data (network centric or end-user centric); (ii) “who” to manage the privacy (user, network operator or service provider); and (iii) “how” to protect privacy (principle of minimum asymmetry, pawS system or P3P). Designers of ubicomp applications need to address carefully these important privacy questions. • Security. Bardram (2005) discussed tradeoffs between usability and security. In the ubicomp environment, we have many public computers serving individual computers. For context awareness systems, users’ details and profiles need to be captured. New design challenges involve understanding security tradeoffs of having users logging into the public computers as opposed to not having authentication where users enjoy access into these various systems. To address these design and implementation challenges, Jones and Marsden (2006) see designers/developers as playwrights developing “scripts” with scenarios and use cases on how technologies are used. Carroll (2000) stresses the importance of maintaining a continuous focus on situations of and consequences for human work and activity to promote learning about the structure and dynamics of problem domains, thus seeing usage situations from different perspectives, and managing tradeoffs to reach usable and effective design outcomes.

23

Ubiquitous Computing History, Development, and Scenarios

Design is difficult and is never completely “done,” resulting in the task-artifact cycle dilemma (Carroll, 2000). This is so because at the start of any software development, tasks help articulate requirements to build artifacts, but designed artifacts create possibilities (and limitations) that redefine tasks. Hence, managing the task-artifact cycle is not a linear endeavour with different starting and ending points. There will always be a further development, a subsequent version, a redesign, a new technology development context. That is, the design scenarios at one point in time are the requirements scenarios at the next point in time. Claims analysis was later developed by Carroll (2000) to enlarge the scope and ambition of scenario-based design approach to provide for more detailed and focused reasoning. Norman’s influential Model of Interaction (Norman, 1988) is used as a framework in claims analysis for questioning the user’s stages of action when interacting with a system in terms of goals, planning, execution, interpretation, and evaluation.

sIngapore as a case exaMple: dIscussIon of scenarIos In educatIon In Singapore, the IT initiatives underwent three phases of implementation in the early 1990s through the Civil Service Computerization Plan, the National IT Plan, and IT 2000. The IT2000 Master Plan was launched in 1992 (National Computer Board, 1992), just 6 months after Weiser’s seminal article on ubicomp in Scientific America (Weiser, 1991). The IT2000 vision in Singapore aimed to provide a nationwide information infrastructure to link every home, school, and workplace in Singapore, creating an intelligent island (Choo, 1997). In 2005, the IT 2000 vision was revised and the Singapore Government Intelligent Nation 2015(iN2015) is a 10-year blueprint to enable every individual to have seamless access to intelligent technology (IDA, 2005). The goal

24

was to create smart, sentient entertainment spaces with networked, embedded spaces padded with sensory and distributed intelligence characterized by human-friendly computing as well as businessefficient automation. In the 2006 survey (IDA Survey, 2006), the high mobile penetration rate of 104.6% of infocomm usage in households and individuals showed that the Internet and mobile phones had perpetually been weaved into the daily activities of Singaporeans. Some examples of innovation usage included (IDA Infocomm Survey, 2006): (i) distributing critical information to the entire population during crisis situations; (ii) voting in contests, donating money during charity events; (iii) booking services for movie or taxi; and (iv) electronic road pricing system utilizing unique vehicle identification units, smart cards, distributed data collection points, and a centralized data centre to provide variable pricing information to drivers going into the central district areas and highways. In education, we are witnessing applications/ services being implemented in some schools in Singapore towards the 2015 vision of making learning truly global and out of the classroom, to align with Singapore’s 10-year Infocomm Plan iN2015 (IDA, 2005a, 2005b, 2006). We illustrate in the following scenarios how different personas could interact with the ubiquitous ecosystem and the contactless smart badge/card as a wearable computer concept that communicates with sensors in the surrounding.

scenario 1 Presently, all school-going students in Singapore possess built-in smart cards, serving as identity cards as well as as cash cards. Kiosks are set up in some schools where students could pay for food using their student cards. These kiosks also record purchasing habits of students. Parents could go online to check expenditures incurred and eating

Ubiquitous Computing History, Development, and Scenarios

habits of their children, attendance records, and homework details.

scenario 2 In the near future, perhaps smart badges with built-in Radio Frequency Identification (RFID) could replace the traditional student card. The smart card storing students’ personal particulars with RFID could automatically send out a unique identifier to sensors located on walls and ceilings in schools. Hundreds of interconnected closed circuit televisions (CCTVs) and images could be installed at every corner in the school to survey and record daily activities, and keep track of incoming or out-going students.

scenario 3 Classrooms could be fully equipped with computing resources involving multimedia features such as screen, pen stylus, and table could be neatly arranged like a Swiss army knife at the side of a chair, and students could scan their smart badges to activate resources. Upon activation, the online learning portal could be launched. The computer could be interconnected to all fellow students and the teacher-in-charge during the class. The portal could allow students to learn, work on their assignments, and take tests or exams in an interactive way. Instead of carrying bags containing books, students could carry tablet PCs, capable of communicating wirelessly with other devices.

scenario 4 Perhaps teachers could also have smart badges with built-in RFIDs and tablet PCs. At the start of school each morning, the tablet PC could automatically take attendance of students in class, and start “tracking down” the absentees. After 15 minutes, it could send a text message via mobile phones to parents concerned. Similarly, parents could remotely find out about their children’s well-

being and whereabout. For example, if a parent wishes to check whether her youngest child at school is having a fever, she could do so by logging onto a portal to activate the smart card for the body temperature to be taken.

conclusIon With all the hype about ubicomp, one could easily get carried away with the lure of benefits it promises to bring. With these challenges, ubicomp also brings along many unknowns and changes radically the way people interact with one another and with the environment. As technology becomes embedded in everyday artefacts, the modes of interaction change constantly. Although Weiser (1991) started the ubicomp vision more than a decade ago, current ubicomp literature keeps revolving around Weiser’s vision for the future of implementing ubicomp applications or services that could provide a seamless interconnected environment. In fact, Bell and Dourish (2006) suggest that we stop talking about the “ubicomp of tomorrow” but rather at the “ubicomp of the present.” Doing so, they advocate getting out of the lab and looking at ubicomp as it is being developed rather than what it might be like in the future. Hence, this chapter highlighted key issues and assessed the current situation of ubicomp development in design architecture and systems, implementation issues, and challenges. Selected scenarios in the Singapore’s education landscape were also described, presenting possibilities and challenges in the future ubiquitous landscape. To conclude, there is perhaps no need for heroic engineering; the heterogeneous technologies could be utilised as well. We are already living in the world of ubicomp. Gibson (1999), father of cyberpunk fiction, rightfully pointed out “the future is here, it is just not evenly distributed” (retrieved on March 11, 2007 from http://en.wikiquote.org/ wiki/William_Gibson).

25

Ubiquitous Computing History, Development, and Scenarios

acknoWledgMent The authors would like to thank the 2006-2007 Usability Engineering Class in the M.Sc. (Information Systems) programme at the Division of Information Studies (Nanyang Technological University) for their discussion on ubiquitous computing.

references Abowd, G. (1999). Software engineering issues for ubiquitous computing. ACM Press. Bardram, J. (2005, July 23). The trouble with login: On usability and computer securityin ubiquitous computing. Springer-Verlag London Limited. Bell, G., & Dourish, P. (2007, January). Yesterday’s tomorrows: Notes on ubiquitous computing’s dominant vision. Personal Ubiquitous Computing, 11(2), 133-143. Carroll, J. (2000). Making use: Scenario-based design of human-computer interactions. The MIT Press. Choo, C.W. (1997). IT2000: Singapore’s vision of an intelligent island. In P. Droege (Ed.), Intelligent environments. North-Holland, Amsterdam. Gadamer, H.G. (1982). Reason in the age of science (Trans.). Cambridge: MIT Press. Heidegger, M. (1955, 1977). The question concerning technology (Trans.). In The question concerning technology and other essays (pp. 3-35). New York: Harper & Row Publishers. IDA. (2005a). Enhancing service, enriching experience, differentiating Singapore. iN2015 (p. 14). Retrieved January 16, 2008, from http://www. in2015.sg/download_file.jsp?file=pdf/11_Tourism_Hospitality_and_Retail.pdf

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IDA. (2005b). Innovation. Integration. Internationalisation. iN2015 (p. 92). Retrieved January 16, 2008, from http://www.in2015.sg/download_file. jsp?file=pdf/01_iN2015_Main_Report.pdf IDA. (2006). iN2015. Retrieved January 16, 2008, from http://www.in2015.sg/about.html IDA Infocomm Survey. (2006). Annual survey of Infocomm usage in households and individuals 2006. Retrieved January 16, 2008, from http:// www.ida.gov.sg/doc/Publications/Publications_ Level2/2006_hh_exec%20summary.pdf Jones, M., & Marsden, G. (2006). Mobile interaction design. John Wiley & Sons Ltd. Keefe, D., & Zucker, A. (2003). Ubiquitous computing projects: A brief history. In Ubiquitous Computing Evaluation Consortium. Arlington, VA: SRI. McCarthy, M. (2005). Adidas puts computer on new footing. Retrieved January 16, 2008, from http://www.usatoday.com/money/ industries/2005-03-02-smart-usat_x.htm Mobile Taiwan Initative. (2004). Retrieved January 16, 2008, from http://www.roc-taiwan.org/uk/ TaiwanUpdate/nsl022005h.htm National Computer Board. (1992). A vision of an intelligent island: IT2000 report. Singapore: National Computer Board. Norman, D. (1998). The psychology of everyday things. Basic Books. Rogers, Y., Price, S., Randell, C., Fraser, D. S., & Weal, M. (2005). Ubi-learning integrates indoor and outdoor experiences. Communications of the ACM, 48(1), 55-59. Rosson, M. B., & Carroll, J. M. (2002). Usability engineering in practice. In Usability EngineeringScenario-Based Development of Human-Computer Interaction (pp. 349-360). San Francisco: Morgan Kaufmann Publishers.

Ubiquitous Computing History, Development, and Scenarios

Want, R., & Pering, T. (2005). System challenges for ubiquitous & pervasive comput-ing. In ICSE’05, ACM 1-58113-963-2/05/00. Weiser, M. (1991). The computer for the twentyfirst century. Scientific American, 265(3), 94104. Weiser, M. (1993a). Some computer science issues in ubiquitous computing. Communications of the ACM, 36(7), 75-84.

Weiser, M. (1993b). Ubiquitous computing. IEEE Computer, 26(10), 7 l-72. Wireless@SG project. (2006). Retrieved January 16, 2008, from http://www.ida.gov.sg/Infrastructure/20070202144018.aspx Yamada, S. (2003). Overview of privacy management. Ubiquitous Computing Environments, National Institute of Informatic.

This work was previously published in Ubiquitous Computing: Design, Implementation, and Usability, edited by Y. Theng & H. Duh, pp. 1-8, copyright 2008 by Information Science Reference (an imprint of IGI Global).

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28

Chapter 1.3

The Ubiquitous Portal Arthur Tatnall Victoria University, Australia

IntroductIon

background

The word portal can be used to represent many different things, ranging from the elaborate entranceway to a medieval cathedral to a gateway to information on the Internet. What all the usages have in common, though, is the idea of facilitating access to some place or some thing. In addition to its use in relation to Web portals, the term can also be used more metaphorically to allude to an entranceway to far away places or new ideas, new knowledge, or new ways of doing things. Some new, or different, ideas, knowledge, or ways of doing things have had a beneficial effect on society, while others have had a detrimental affect. A portal can thus lead to various different places, things, or ideas, both good and bad. Before a portal can be used, however, it must be adopted by the individual or organisation concerned, and adoption of technological innovations such as portals is the subject of this article.

Gateways come in all shapes and sizes, and likewise so do portals. Portals are seen everywhere (Tatnall, 2005a) and it would be difficult to make any use of the Web without encountering one. On the Web there are government portals, science portals, environmental portals, community portals, IT industry portals, professional society portals, education portals, library portals, genealogy portals, horizontal industry portals, vertical industry portals, enterprise information portals, medical and health portals, e-marketplace portals, personal/mobile portals, information portals, niche portals, and many more. Portals have become truly ubiquitous. In literature and film also, many mentions are made of portals, although not all of the Web variety. These range from a description of the sun by William Shakespeare in Richard II (Act 3, Scene 3): “See, see, King Richard doth himself appear, as doth the blushing discontented sun from out

Copyright © 2010, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

The Ubiquitous Portal

the fiery portal of the east.” (Shakespeare, 1595), to the means of moving around the universe in the TV series Stargate SG-1. The transportation device used by Ford Prefect and Arthur Dent in the Hitch Hiker’s Guide to the Galaxy (Adams, 1979) could also be considered a portal, as could the teleport mechanism employed by the crew leaving or returning to the Enterprise in Star Trek. In much science fiction and fantasy literature, a portal-like device is used to move from one place to another without the need for inconvenient (or perhaps impossible) explanations of the means of doing so. The portal (whether or not it is called this) is thus used as a black box (Latour, 1996) capable of almost magical transformations. In many ways, a Web portal can also be considered as a black box that achieves its purpose of taking a user to some interesting or useful place on the Web without them needing to know how this is done. For most people, other than those involved in their design or construction, the technology of the Web portals is irrelevant. All they want to know is that it provides a convenient means of taking them to some Web location where they want to go. Just because a portal exists, however, there is nothing automatic about organisations or individual people wanting to adopt or use it. A portal will only be adopted if potential users make a decision to do so, and such decisions are not as simple as one might naively think. Adoption of a technological innovation, such as a portal, occurs for a variety of reasons, and this is a significant study in itself. The first step to researching the use of a portal by an organisation (or individual), though, is to investigate why it was adopted. The remainder of this article will consider the portal as a technological innovation and consider portal adoption through the lens of innovation theory.

the portal as a technologIcal InnovatIon Many people use the words invention and innovation almost synonymously, but for any academic discussion of technological innovation an important distinction needs to be made between these terms. Invention refers to the construction of new artefacts or the discovery of new ideas, while innovation involves making use of these artefacts or ideas in commercial or organisational practice (Maguire, Kazlauskas, & Weir, 1994). Invention does not necessarily invoke innovation and it does not follow that invention is necessary and sufficient for innovation to occur (Tatnall, 2005b). Clearly the portal can be seen as an invention, but the point here is that it will not be used unless it is adopted, and that means looking at it also as a technological innovation. Of course, the application of innovation theory to the adoption of a technological innovation assumes that the potential adopter has some choice in deciding whether or not to make the adoption. In the case of an organisation or individual considering the adoption and use of a portal, however, it is difficult to see any reason why they would not have a large measure of choice in this adoption decision. This makes the application of adoption theory quite appropriate when considering the use of Web portals.

adoptIon of technologIcal InnovatIons There are a number of theories of technological innovation, diffusion of innovations (Rogers, 1995) probably being the best known. Other innovation theories include the technology acceptance model (Davis, 1989; Davis, Bagozzi & Warshaw, 1989) and innovation translation (Callon, 1986b; Latour, 1996; Law, 1991), informed by actor-network theory (ANT).

29

The Ubiquitous Portal

Innovation diffusion Innovation diffusion is based on the notion that adoption of an innovation involves the spontaneous or planned spread of new ideas, and Rogers defines an innovation as: “... an idea, practice, or object that is perceived as new” (Rogers, 1995, p. 11). In diffusion theory the existence of an innovation is seen to cause uncertainty in the minds of potential adopters (Berlyne, 1962), and uncertainty implies a lack of predictability and of information. Diffusion is considered to be an information exchange process among members of a communicating social network driven by the need to reduce uncertainty (Rogers, 1995). Rogers elaborates four main elements in innovation diffusion: characteristic of the innovation itself, the nature of the communication channels, the passage of time, and the social system through which the innovation diffuses (Rogers, 1995). Innovation diffusion has had considerable success in explaining large scale movements and adoptions, but has been found less successful when considering adoption by individual organisations and people.

Technology Acceptance Model The technology acceptance model (TAM) is a theoretical model that evaluates “… the effect of system characteristics on user acceptance of computer-based information systems” (Davis, 1986, p. 7). It was developed from the theory of reasoned action (Fishbein & Ajzen, 1975). TAM assumes that a technology user is generally quite rational and uses information in a systematic manner to decide whether to adopt a given technology. Davis’s (1986) conceptual framework proposed that a user’s motivational factors are related to actual technology usage, and hence act as a bridge between technology design (including system features and capabilities) and actual technology usage. Davis (1986) posits that perceived useful-

30

ness and perceived ease of use are major determinants of technology acceptance. Like innovation diffusion, TAM places considerable importance on the “innate” characteristics of the technology and so is based on an essentialist position (Grint & Woolgar, 1997).

Innovation translation An alternative view of innovation is that of innovation translation proposed in actor-network theory (ANT), that considers that the world is full of hybrid entities (Latour, 1993) containing both human and nonhuman elements. ANT developed around problems associated with attempts to handle socio-technical “imbroglios” (Latour, 1993) like electric cars (Callon, 1986a), scallop fishing (Callon, 1986b), Portuguese navigation (Law, 1987), and supersonic aircraft (Law & Callon, 1988) by regarding the world as heterogeneous (Chagani, 1998). ANT offers the notion of heterogeneity to describe projects such as the adoption of portal technology, which involves computer technology, the Internet, the Web portal, broadband connections, Internet service providers (ISP), and the individual or organisation considering the adoption. More specifically though, ANT makes use of a model of technological innovation which considers these ideas along with the concept that innovations are often not adopted in their entirety but only after “translation” into a form that is more appropriate for the potential adopter. The core of the actor-network approach is translation (Law, 1992), which can be defined as: “... the means by which one entity gives a role to others” (Singleton & Michael, 1993, p. 229). Rather than recognising in advance supposed essential characteristics of humans and of social organisations and distinguishing their actions from the inanimate behaviour of technological and natural objects (Latour, Mauguin, & Teil, 1992, p. 56), ANT adopts an antiessentialist position

The Ubiquitous Portal

in which it rejects there being some difference in essence between humans and nonhumans. ANT makes use of the concept of an actor (or actant) that can be either human or nonhuman, and can make its presence individually felt by other actors (Law, 1987). It is often the case that when an organisation (or individual) is considering a technological innovation they are interested in only some aspects of this innovation and not others (Tatnall, 2002; Tatnall & Burgess, 2002). In actor-network terms it needs to translate (Callon, 1986b) this piece of technology into a form where it can be adopted, which may mean choosing some elements of the technology and leaving out others. What results is that the innovation finally adopted is not the innovation in its original form, but a translation of it into a form that is suitable for use by the recipient (Tatnall, 2002). Innovation Translation can be considered to proceed through several stages. In the first stage, the problem is redefined, or translated, in terms of solutions offered by these actors (Bloomfield & Best, 1992) who then attempt to establish themselves as an “obligatory passage point” (Callon, 1986b) which must be negotiated as part of its solution. The second stage is a series of processes which attempt to impose the identities and roles defined in the first stage on the other actors. It means interesting and attracting an entity by coming between it and some other entity (Law, 1986). If this is successful, the third stage follows through a process of coercion, seduction, or consent (Grint & Woolgar, 1997) leading to the establishment of a solid, stable network of alliances in favour of the innovation. Finally, the proposed solution gains wider acceptance (McMaster, Vidgen, & Wastell, 1997) and an even larger network of absent entities is created (Grint & Woolgar, 1997) through some actors acting as spokespersons for others.

researchIng the adoptIon of Web portals Both innovation diffusion and the technology acceptance model suggest that adoption decisions are made primarily on the basis of perceptions of the characteristics of the technology concerned (Davis 1989; Rogers 1995). Using an innovation diffusion approach, a researcher would probably begin by looking for characteristics of the specific portal technology to be adopted, and the advantages and problems associated with its use. They would think in terms of the advantages offered by portals in offering a user the possibility of finding information, but would do so in a fairly mechanistic way that does not allow for an individual to adopt the portal in a way other than that intended by its proponent; it does not really allow for any form of translation. If using TAM, this researcher would similarly have looked at characteristics of the technology to see whether the potential user might perceive it to be useful and easy to use. A researcher using an innovation translation approach to studying innovation, on the other hand, would concentrate on issues of network formation, investigating the human and nonhuman actors and the alliances and networks they build up. They would attempt to identify the actors and then to follow them (Latour, 1996) in identifying their involvement with the innovation and how they affect the involvement of others. The researcher would then investigate how the strength of these alliances may have enticed the individual or organisation to adopt the portal or, on the other hand, to have deterred them from doing so (Tatnall, 2002; Tatnall & Burgess, 2006; Tatnall & Gilding, 1999).

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The Ubiquitous Portal

conclusIon Web portals are now quite ubiquitous, and researching their use in organisations and by individuals is an important aspect of information systems research. It is useful to consider the portal as a technological innovation and to research it using an approach based on innovation theory. The question is, which innovation theory is most appropriate? Both innovation diffusion and the technology acceptance model rely on the idea that the technology involved, in this case the Web portal, has some underlying immutable characteristics or essences that a potential user takes into consideration when making adoptions decisions. Innovation Translation, informed by actor-network theory, offers instead an antiessentialist socio-technical approach. In this article, I have put the view that it is this approach that is most useful when researching the adoption and use of portals. The innovation translation approach is particularly useful in considering that topic, people, and technology are intimately involved with each other and their individual contributions to the innovation decision are difficult to differentiate . The question of whether “ideas portals,” or the metaphorical entrance ways to new ideas, new knowledge or new ways of doing things, could usefully be researched using actor-network theory is unanswered. ANT could perhaps investigate which of these have had a beneficial affect on society and which have had a detrimental affect. This could involve an interesting topic for another research paper.

references Adams, D. (1979). The hitch-hikers guide to the galaxy. London: Pan Books.

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Berlyne, D. E. (1962). Uncertainty and epistemic curiosity. British Journal of Psychology, 53, 2734. Bloomfield, B. P., & Best, A. (1992). Management consultants: Systems development, power and the translation of problems. The Sociological Review, 40(3), 533-560. Callon, M. (1986a). The sociology of an actornetwork: The case of the electric vehicle. In M. Callon, J. Law, & A. Rip (Eds.), Mapping the dynamics of science and technology (pp. 19-34). London: Macmillan Press. Callon, M. (1986b). Some elements of a sociology of translation: Domestication of the scallops and the fishermen of St Brieuc Bay. In J. Law (Ed.), Power, action & belief: A new sociology of knowledge? (pp. 196-229). London: Routledge & Kegan Paul. Chagani, F. (1998). Postmodernism: Rearranging the furniture of the universe. Irreverence, 1(3), 1-3. Davis, F. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results. Doctoral thesis, MIT, Boston. Davis, F. D. (1989, September). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 318340. Davis, F. D., Bagozzi, R., & Warshaw, P. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading: Addison-Wesley. Grint, K., & Woolgar, S. (1997). The machine at work—Technology, work and organisation. Cambridge: Polity Press.

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Latour, B. (1993). We have never been modern. Hemel Hempstead: Harvester Wheatsheaf. Latour, B. (1996). Aramis or the love of technology. Cambridge, MA: Harvard University Press. Latour, B., Mauguin, P., & Teil, G. (1992). A note on socio-technical graphs. Social Studies of Science, 22(1), 33-57. Law, J. (1986). The heterogeneity of texts. In M. Callon, J. Law, & A. Rip (Eds.), Mapping the dynamics of science and technology (pp. 67-83). London: Macmillan Press. Law, J. (1987). Technology and heterogeneous engineering: The case of Portuguese expansion. In W. E. Bijker, T. P. Hughes, & T. J. Pinch (Eds.), The social construction of technological systems: New directions in the sociology and history of technology (pp. 111-134). Cambridge, MA: MIT Press. Law, J. (Ed.) (1991). A sociology of monsters. Essays on power, technology and domination. London: Routledge. Law, J. (1992). Notes on the theory of the actornetwork: Ordering, strategy and heterogeneity. Systems practice, 5(4), 379-393. Law, J., & Callon, M. (1988). Engineering and sociology in a military aircraft project: A network analysis of technological change. Social Problems, 35(3), 284-297. Maguire, C., Kazlauskas, E. J., & Weir, A. D. (1994). Information services for innovative organizations. San Diego, CA: Academic Press. McMaster, T., Vidgen, R. T., & Wastell, D. G. (1997). Towards an understanding of technology in transition: Two conflicting theories. In Proceedings of the Information Systems Research in Scandinavia, IRIS20 Conference, Hanko, Norway, University of Oslo.

Shakespeare, W. (1595). Richard II. The complete works of Shakespeare (pp. 358-384). London: Spring Books. Singleton, V., & Michael, M. (1993). Actornetworks and ambivalence: General practitioners in the UK cervical screening programme. Social Studies of Science, 23, 227-264. Tatnall, A. (2002). Modelling technological change in small business: Two approaches to theorising innovation. In S. Burgess (Ed.), Managing information technology in small business: Challenges and solutions (pp. 83-97). Hershey, PA: Idea Group Publishing. Tatnall, A. (2005a). Portals, portals everywhere…. In A. Tatnall (Ed.), Web portals: The new gateways to Internet information and services (pp. 1-14). Hershey, PA: Idea Group Publishing. Tatnall, A. (2005b). To adopt or not to adopt computer-based school management systems? An ITEM research agenda. In A. Tatnall, A. J. Visscher, & J. Osorio (Eds.), Information technology and educational management in the knowledge society (pp. 199-207). New York: Springer-Verlag. Tatnall, A., & Burgess, S. (2002). Using actornetwork theory to research the implementation of a B-B Portal for regional SMEs in Melbourne, Australia. In Proceedings of the 15th Bled Electronic Commerce Conference—‘eReality: Constructing the eEconomy’. Bled, Slovenia: University of Maribor. Tatnall, A., & Burgess, S. (2006). Innovation translation and e-commerce in SMEs. In M. Khosrow-Pour (Ed.), Encyclopedia of e-commerce, egovernment and mobile commerce (pp. 631-635). Hershey, PA: Idea Group Reference.

Rogers, E. M. (1995). Diffusion of innovations. New York: The Free Press.

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Tatnall, A., & Gilding, A. (1999). Actor-network theory and information systems research. In Proceedings of the10th Australasian Conference on Information Systems (ACIS). Victoria University of Wellington.

key terMs Actor (Actant): An entity that can make its presence individually felt by other actors. Actors can be human or nonhuman. Nonhuman actors include such things as computer programs, portals, organisations, and other such entities. An actor can be seen as an association of heterogeneous elements that constitute a network. This is especially important with nonhuman actors, as there are always some human aspects within the network. Actor-Network Theory (ANT): An approach to socio-technical research in which networks, associations, and interactions between actors (both human and nonhuman) and are the basis for investigation.

Black Box: A concept whereby some object or idea is considered only in an external manner in relation to the affect it produces, without reference to what goes on inside it. This simplification enables the study of complex entities without worrying too much about their internal working details when this is not entirely necessary. Innovation Diffusion: Is considered to be an information exchange process among members of a communicating social network driven by the need to reduce uncertainty. Innovation Translation: An innovation is often not adopted in its original form, but as a “translation” of this original into a form that is found to be suitable for use by the recipient. Invention: Refers to the construction of new artefacts or the discovery of new ideas. Technological Innovation: Involves making use of these artefacts or ideas in commercial or organisational practice. Technology Acceptance Model (TAM): Considers that adoption decisions are determined primarily by a consideration of perceived usefulness and perceived ease of use.

This work was previously published in Encyclopedia of Portal Technologies and Applications, edited by A. Tatnall, pp. 10401044, copyright 2007 by Information Science Reference (an imprint of IGI Global).

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Chapter 1.4

The Ubiquitous Grid Patricia Sedlar Johannes Kepler University, Austria

vIsIon Grid computing is an emerging technology providing the possibility to aggregate resources for the solution of computation- or data-intensive scientific tasks. Taking the evolution of mobile computing into consideration, new Grid concepts are conceivable, fully exploiting the advantage of mobile devices and ubiquitous access. By decoupling resource availability from the core grid infrastructure and hardware, the user has always the same computational power, data or storage available, regardless of a device or location. Thus restricted capabilities of thin clients can be extended and new fields of application can be made accessible. The key concept is “The invisible grid” – the grid environment should just be there for the use of applications in science, business, health care, environment, or culture domains. Having this concept in mind, the following scenario is conceivable: Equipped with your mobile phone,

which you always have with you, you are walking around and are taking a picture of an object you are interested in. You are sending the picture to the grid, where the visual information is extracted. After the analysis, information about the captured object is sent to you. Thus you have a search engine on a visual base at your permanent disposal, information captured as seen by your eyes – without the need of textural translations or the need to know the object’s name or ID in order to retrieve information about it. Realizing the scenario above, the user obtains a smart tool, easing information retrieval considerably by making use of ubiquity in combination with grid computing. But the scenario has even more potential in terms of pervasiveness. The use of mobile devices can provide a user with additional location bound information. With a portable device the user is able to access location-based services or to collect environmental information to be processed within a grid. At this stage research activities in the field of pervasive computing come

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The Ubiquitous Grid

into play. Pervasive computing pursues the goal to enhance the environment with sensors and smart objects in order to provide the user with suitable context-based and/or location-based services. Expanding the introduced setting with the capabilities from pervasive computing, the following scenario is conceivable: You are an invited speaker on a conference and you are moving through the rooms of the venue. All rooms are equipped with cameras covering all perspectives of view. You are looking at a person from whom you want to know the research interests. You flick with your finger, to capture the camera picture from your perspective. The picture is processed within the grid and the ambient display next to you shows the requested information.

net. By using a grid of computers, it is possible to aggregate computational power to generate a huge virtual multi-computer ready for processing, storage, and communication. Since a grid can be made up of a set of geographically separate networks, enormous computational power can be made available for solving complex or data intensive problems. Grid computing is still at its early stages of evolution. Anyhow it is no longer the exclusive realm of researchers aiming to solve sophisticated scientific tasks (Gentsch, 2004). Alike the evolution of the Internet, main grid initiatives aim to successively establish a global grid, providing users with infinite resources, just by plugging the computer.

Pervasive Computing IntroductIon The scenarios described in the foregoing section aim to combine strengths of three main disciplines: grid computing, pervasive computing, and mobile computing.

Grid Computing The term “grid” was coined in the mid-1990s to refer to a proposed distributed computing infrastructure for advanced science and engineering (Foster & Kesselman, 2004). A grid is an infrastructure of geographically distributed resources, comprising hardware components such as processors, memory media, or scientific instrumentation and software components such as services, applications, licenses, and so forth. Its infrastructure consists of hard- and software elements to aggregate and to coordinate resources. The first grid that has been developed, for the European Organization for Nuclear Research (CERN) to support the research of the particle physics laboratory (Colasanti, 2004), uses a large scale distributed system by taking the advantage of the rich infrastructure provided by the Inter-

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Pervasive computing was inspired by Mark Weiser in 1991, when he introduced his vision of the computer of the 21st century with the central statement: “The most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are indistinguishable from it” (Weiser, 1991). His assumption that, “we are trying to conceive a new way of thinking about computers in the world, one that takes into account the natural human environment and allows the computers themselves to vanish into the background” has fertilized the embedding of ubiquitous computing technology into a physical environment which responds to people’s needs and actions (Ferscha, 2003). To bring interaction “back to the real world” (Wellner et al., 1993) was the second historical vision impacting the evolution of pervasive computing. Instead of interacting with digital data via keyboard and screen, physical interaction with digital data, for example, via “graspable” or “tangible” interfaces, was proposed (Ferscha, 2003). Present research activities in the field of pervasive computing aim to enhance the human

The Ubiquitous Grid

with embedded, intelligent “smart objects,” detecting user needs and initializing all necessary processes. The “home of the future” is a popular field of application. You wake up in the morning, the sensors of the coffee machine detect that you urgently need a coffee and starts brewing. The refrigerator prints a shopping list of items missing; the sensors of your pajama send an e-mail to your wardrobe, recommending the colour best complementing your mood in order to select the most suitable clothing for today, and so forth.

Mobile Computing The foregoing section introduced the objectives of pervasive computing. Its aim is to establish an enhanced environment, autonomously detecting user needs and reacting on them. In order to fulfil this goal, pervasive computing applications have to provide ubiquitous access, context awareness, intelligence, and natural interaction (Ferscha, 2003). At this early stage of research, we are far from global concepts allowing users to interact with arbitrary pervasive computing environments. In order to interact with smart objects, personalization is frequently done at the base of profiles saved on mobile devices. Due to this fact, and our aim to build the ubiquitous grid on the strengths of existing technologies, mobile computing will be part of the initial concept.

Interaction Model The proposed ubiquitous grid is an intersection of grid computing and pervasive computing. With the mobile device, the user may initialize interaction between these domains (see Figure 1). Referring to the scenarios introduced at the beginning of the chapter, the user is taking a picture, and sends it to a grid application using his mobile device. The information is processed within the grid, and the result is then returned to the user directly or handled to the pervasive computing environment.

Figure 1. Interaction model

grId coMputIng Grid Applications In the following, we are going to give a brief survey of traditional fields of grid computing, which require extensive computational power and/or storage, and show some examples of high performance applications that can be provided by PC clusters: Medicine: Medical simulations and visualizations are a large field of grid applications. They typically require computational power usually not available in a hospital. An example of such application is a virtual vascular surgery on the grid, allowing pre-treatment planning through real-time interactive simulation of vascular structure and flow. The system – set up on a computational grid – consists of a distributed real-time simulation environment, in which a user interacts in virtual reality (IFCA, 2004). Physics: An example of an application using a data grid can be found in the field of high energy physics. One of its main challenges is to answer questions about fundamental particles and the forces acting between them. To that purpose a grid can host a powerful particle accelerator, which will provide data related to these interactions at a tremendous output rate and the data grid provides the solution for storing and processing such a huge amount of data (IFCA, 2004). Computer Graphics: The rapid development and low price of personal computers make it an

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The Ubiquitous Grid

interesting choice to convey ideas through visualization. As real-time 3-D graphics are adequate for many applications, a single computer is often insufficient if photo-realistic images are required. With grid-based distributed computing it is possible to produce fast, cheap photo-realistic images, using the processing power of office computers being idle (Pennanen & Ylikerälä, 2004). Education: Another field of interest for grid computing is education. Providing a semantic data grid for human learning, the implementation of future learning scenarios based on ubiquitous, collaborative, experimental-based and contextualized learning can be supported (Ritrovato & Gaeta, 2004).

Mobility and ubiquity in the context of Grid Computing Compared to traditional (wired) grids, mobile grids have the advantage of exploiting the concepts of mobility and ubiquity in terms of being available anytime, anywhere, and by all means. Making use of wireless connection, the mobile grid environment is available anytime and anywhere. Nevertheless there is a lack of applications that can be attributed to the crucial disadvantage that a mobile grid cannot rely on stable basic conditions. It has to cope with variable resource availability and different types of user terminals. As each combination of resources and user devices brings its specific restrictions and challenges, the selection of an adequate grid integration and an appropriate application will be dependant on the following criteria: Type of job processing: Job processing of a computational grid can be done in two different ways, either sequential, by a narrow set of repetitive tasks or in a true parallel, distributed fashion in order to execute a complex job (Ault & Tumma, 2004). In the first case, jobs can be processed by a single terminal; in the second case jobs may be processed faster, but implies

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coordination between cooperating terminals. The usage of parallel computing for mobile grids poses a big challenge, because it requires a very robust, possibly performance consuming resource management taking into account log-offs and location changes of mobile nodes. Type of network: Another requirement that need to be taken care of while designing a mobile grid is the type of network. A fix, wired network allows a prediction of computational power and storage space. Resources of an ad-hoc grid can vary strongly according to the current network topology and cannot offer QoS. Type of connection: As for the type of network, physically distributed terminals offer the advantage of predictable and mostly reliable connections. However wireless connections allow ubiquitous access to services. Application requirements: Central aspects to choose an adequate grid integration are the applications requirements. Parameters to be considered are: •

•

•

Data size: This refers to the amount of data to be computed, transmitted, stored and/or visualized. QoS: This parameter includes all requirements concerning quality of service and refers to performance and/or reliability of services. Ubiquity: The last parameter identifies the accessibility of services (catch phrase: anytime, anywhere).

Type of user device: As mobile devices often have restrictions in regard to their capacities, it might be necessary to check, if a portable device fulfils an applications requirements in terms of battery capacity, display size and memory size.

Potential for Mobility Support In the context of the AGrid project1, we conducted

The Ubiquitous Grid

a survey of the potential for mobility support for scientific grid applications. The objective of the AGrid project is to promote and to develop grid technologies within Austria. To meet this objective, technology-oriented work packages act in strong cooperation with application-oriented work packages in order to be able to adequately address the needs of the users. For the elicitation of application of application demands, structured interviews have been done within the mobility work package with all application work packages. The questionnaire used for these interviews addressed the following issues: 1) Description of the application, 2) execution time and real-time requirements, 3) data, 4) availability, 5) security, 6) user interface and data input, 7) software and hardware architecture, 8) network, 9) performance measures and 10) mobility. These interviews covered the following spectrum of applications: • • • • • • • • • • • • •

Distributed Heart Simulation Virtual Lung Biopsy Virtual Eye Surgery Medical Multimedia Data Management and Distribution Virtual Arterial Tree Tomography and Morphometry High-Energy Physics Distributed Scientific Computing: Advanced Computational Methods in Life Science Computational Engineering High Dimensional Improper Integration Procedures Astrophysical Simulations and Hydrodynamic Simulations Federation of Distributed Archives of Solar Observation Meteorological Simulations Environmental Grid Application

Through the interviews with all application groups, we came to the following summary: Most

of the groups have special application needs in terms of data intensity, real-time interaction, and/or visualization. As a consequence, main interaction processes can only be done with the aid of desktop computers. As tasks performed within grids typically take several hours, some groups indicated interest in mobility support for observing and monitoring or for job relaunch upon failure. Additionally, a couple of groups could imagine using lightweight devices for mobile data collection. Analyzing these results, we came to the conclusion that mobility support for typical grid applications is of minor relevance. It can serve to support interaction processes carried out on desktop machines but has little added value for scientific grid applications (Sedlar & Kotsis, 2007).

pervasIve approach for grId coMputIng Dealing with grid computing, people frequently face issues hindering practical usage of grid. The core grid infrastructure is set up of a network of high performance nodes while resources remain largely unused. Frequently given reasons are the missing of maturity of grid technologies in terms of: •

•

Security: Providing data and/or computational power across administrative domains entails severe security hazards. Storage of sensitive data and the execution of foreign code is still a delicate issue. Legal aspects: Numerous legal aspects need to be defined in order to regulate interactions within grids; for example, how to handle environmental data designated to calculate transnational meteorologic models, not being allowed to be handled outside of country frontiers. Or who is to be called for account

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The Ubiquitous Grid

•

•

•

when a grid is flooded by hacking attacks or DOS-attacks? Usability: Grid applications are far from being plug and play applications. They often have a tremendous administrative overhead and complexity overchallenging non-computer scientist end users. Performance guarantees: As the goal of grid computing is to manage dynamically changing resources, performance cannot be guaranteed. Billing mechanisms: This aspect goes inline with missing performance guarantees. A provider of a time-critical application cannot charge his clients, when the performance of the grid cannot be guaranteed.

Having a look in the field of pervasive computing, you find numerous applications at the first sight. The vision, to be surrounded by smart objects, detecting your needs, and initializing all necessary processes, is very tempting and we estimate pervasive computing to be a seminal field of research. Anyhow those smart objects are still not part of our every day life. Research activities in this area primarily concentrate on feasibility studies of futuristic nice-to-have-things. They currently don’t deliver ready to use technologies and factor out usability aspects (Truong et al., 2004). In terms of mobility the inclusion of lightweight devices is often not taken into consideration due to restrictions concerning storage and performance capabilities, screen size, input modalities, battery size, and the additional complexity in order to cope with log-on, log-offs and location changes of mobile user terminals. The above research results and arguments justifying the lack of applications lead us to the following conclusions:

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1.

2.

3.

A typical approach for developing mobile applications is to concentrate on the tasks at hand rather than on how these tasks are implemented. Pursuing this method, we face restrictions from lightweight devices and furthermore supplementary mechanisms need to be included in order to cope with major drawbacks. Anyhow tasks cannot be completed with the traditional convenience of desktop computing and hence applications are thought to be dissatisfying. Pervasive computing concentrates on tasks, we usually do without the aid of computers. At this early stage of research, there are no mature, easy to use technologies and additionally we are not used to them. But we expect that the future will bring a lot of technologies that will make this vision possible. In consideration of the fact that there is a lack of “ready to use” applications and technologies leveraging mobile users in both fields, we suggest to choose a more user centered approach and to concentrate on tasks we typically do with the aid of mobile devices. In order to design a satisfactory application, the following factors can enhance the user’s acceptance: • Technologies: There are a lot of mature technologies. Making use of them may enhance the user’s convenience and prevents from technical infirmity reducing the user’s acceptance. • Interaction: The use of proved, empirically tested interaction modes enhances the usability of systems significantly (Sedlar, 2004). • Usage trends: Taking usage trends into consideration means to respond to user needs and thus provide a proper user centering.

The Ubiquitous Grid

dIscussIon of approaches A ubiquitous grid can be realized in two different ways:

Implicit Approach The following approach is based on pervasive computing infrastructure, providing an environment enhanced with smart objects, able to communicate. These entities are designed to initiate interaction upon matching with the user profile(s). Taking up this concept, smart objects could be activated upon visual recognition. For example, a user can take a picture of an entity of interest and send it to the grid in order to be processed. Having extracted the visual information, the corresponding smart object is activated. This approach has the advantage that no user profiling is needed in order to retrieve contextbased information (Schmidt, 2000). Instead of providing accurate filters for push-information based on complex user profiles, the system offers content on-demand. Furthermore it profits from technical advances in the field of pervasive computing, aiming natural device independent interaction and thus serves as a base to detach interaction from mobile devices. Pursuing this concept, the main disadvantage is that all objects need to be enhanced for information retrieval. Due to the fact that environments equipped with smart objects are rare at this early stage of research in the field of pervasive computing, we envisage the following approach in order to realize a first prototype of a ubiquitous grid.

User Controlled Approach This approach is designed to work independently from the pervasive computing environment. Thus no smart objects are involved to deliver context- or location-bound information (Schmidt, 2000). Considering the example scenario as outlined in the introduction, an information request is

conveyed through pictures. Referring to MPEG7 research results it becomes obvious that visual content extraction without the provision of context information is not accurate enough yet (Lew et al., 2006). Having a concept in mind, which is neither restricted to a specific context nor needs to be adapted to a particular application, we propose to make use of the information of context a user personally has. For example a user is taking a picture of a leaf in order to retrieve the name of the tree the leaf is from. The user doesn’t need a content extraction telling her that the item on the picture is a leaf. Incorporating the user’s knowledge about context corresponds to the functionality of an Internet search engine. Here the user also enters all known keywords in order to retrieve suitable information. Following this methodology, three approaches can be conceived: 1. 2.

3.

Visual information is annotated with additional keywords. Visual information is sent to the appropriate application. Referring to the example introduced above, the picture is sent to an application providing information about leaves. The user chooses keywords to obtain a list of available applications. For example, the user enters the keyword “leaf” and the system returns a list with the applications “leaf recognition (tree)” and “leaf recognition (flower).”

The third approach is preferred over the other two because it best supports the user needs and will deliver the most accurate results.

applIcatIon scenarIo Analyzing the SWOT2 attributes one can envision the following setting and scenario:

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The Ubiquitous Grid

As most people are in the possession of a mobile phone with at least average capabilities, the focus will be on these devices. They can communicate and handle data over wireless connections, have networking capabilities, send and receive SMS, and are able to take reasonable pictures. As for the interaction modes we will use SMS and the handhelds capability of taking pictures. SMS was conceived as add-on for mobile phones and nobody believed that someone could use this feature instead of a short phone call. Actually it became a worldwide hype by providing discrete, anonymous and ubiquitous communication. In order to preserve these characteristics, we chose the handhelds capability of taking pictures, complementing the communication with SMS as a discrete, accepted and natural interaction mode. In line with user demands, we took up the trend one step further towards business networking as a base for the application scenario below. Aside from presenting own results and getting up to date with other ongoing activities, a main aim of a conference is to get in touch with other similar minded researchers to discuss current topics of interest. This task can be supported by providing you with professional background information of a participant when requested and can be realized as follows: During the coffee break you see a person you are interested in. You are taking a picture and you process it within the grid. Promptly you get an SMS with the affiliation and research interests of the participant.

conclusIon and future prospects In this chapter we have studied the potential of the application and lessons learned from mobile computing and ubiquitous computing in the realm of grid computing. The project from which this paper stemmed aims to promote and to develop

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grid technologies within Austria; in which a questionnaire and interviews have been conducted to determine the feasibility of a spectrum of grid applications. This chapter goes one step further to identify the application domains and the requirements of these applications in the context of mobile and ubiquitous computing. These requirements are both intrinsic and external to the nature of mobile and ubiquitous computing, such as network requirements, service requirements and application requirements. The main contribution of this research is to identify the integration patterns of the mobile grid and to propose a theoretical and practical approach on how to realize it. In the future the architecture of such approach will be proposed and the application scenarios will be extended in a way that fill the gap between the technology promises and user expectations, including issues such as security, legal aspects, or usability.

references Ault, M., & Tumma, M. (2004). Oracle 10g grid & real application clusters. Rampant Techpress. Colasanti, F. (2004). Grids: A crucial technology for science and industry. ERCIM News, (59), 3. Ferscha, A. (2003). What is Pervasive Computing? Peter Rechenberg Festschrift zum 70 (pp. 93-108). Geburtstag, Universitätsverlag Rudolf Trauner. Foster, I., & Kesselman, C. (2004). Grid2: Blueprint for a new computing infrastructure (2nd Ed.). Morgan Kaufmann. Gentsch, W. (2004). Grid: Defining the future of the Internet. GRIDtoday, 3(33). IFCA Institute of Physics of Cantabria. (2004). Grid projects. Retrieved from http://grid.ifca. unican.es/dissemination/Grid\_Projects\_home. htm.

The Ubiquitous Grid

Lew, M.S., Sebe, N., Jjeraba, C., & Jain, R. (2006). Content-based multimedia information retrieval: State of the art and challenges. New York: ACM Press. Pennanen, M., & Ylikerälä. (2004). Photorealistic visualization with grid-based technology. ERCIM News, (59), 51-52. Ritrovato, P., & Gaeta, M. (2004). The European learning grid infrastructure integrated project. ERCIM News, (59), 24-25. Schmidt, A. (2000). Implicit interaction through context. Personal Technologies, 4(2). Sedlar, P., & Kotsis, G. (2007). The ubiquitous grid. In Proceedings of the 5th Annual Conference on Advances in Mobile Computing and Multimedia, MOMM 2007, Jakarta, Indonesia (pp. 113-125). Sedlar, P. (2004). Dialoggesteuerte Schnittstellen für mobiles Lernen. Master’s thesis, Fachhochschule Hagenberg, Austria. Truong, K.N., Huang, E.M., Stevens, M.M., & Abowd, G.D. (2004). How do users think about ubiquitous computing? Extended Abstracts of ACM Human Factors in Computing Systems: CHI 2004 (pp. 1317-1320). Weiser, M. (1991). The computer of the 21st century. Scientific American, pp. 94-100. Wellner, P., Mackay, W., & Gold, R. (1993). Computer augmented environments: Back to the real world. Communications of the ACM, 36(7).

Grid Computing: A grid is an infrastructure of geographically distributed resources, comprising hardware components to aggregate and to coordinate resources. By using a grid of computers, it is possible to aggregate computational power to generate a huge virtual multi-computer ready for processing, storage, and communication. MPEG 7: Is formally called “Multimedia Content Description Interface.” It is a multimedia content description standard developed to describe content itself and thus allow fast and efficient searching for material that is of interest to the user. Pervasive Computing: Pervasive computing aims to develop interaction paradigms, where information processing has been thoroughly integrated into everyday objects and activities, allowing computers to vanish into the background. Smart Objects: Intelligent artefacts, embedded in a pervasive computing environment, detecting user needs and initializing all necessary processes. Usability: Is an equivalent to “user friendliness” and denotes the ease with which people can employ a tool or an object in order to achieve a particular goal. User Profile: Or simply “profile” is a collection of personal settings enabling the personalization of a system.

endnotes key terMs

1 2

Context: Context comprises relevant information about a service’s situation of use, for example information about the user’s interest, device’s display capabilities, or geographic location of service invocation.

http://www.austriangrid.at/ Strengths, Weaknesses, Opportunities and Threats

This work was previously published in Handbook of Research on Mobile Multimedia, Second Edition, edited by I. Ibrahim, pp. 66-75, copyright 2009 by Information Science Reference (an imprint of IGI Global). 43

44

Chapter 1.5

RFID Technologies and Applications Christian Kaspar Georg-August-Universität Göttingen, Germany Adam Melski Georg-August-Universität Göttingen, Germany Britta Lietke Georg-August-Universität Göttingen, Germany Madlen Boslau Georg-August-Universität Göttingen, Germany Svenja Hagenhoff Georg-August-Universität Göttingen, Germany

IntroductIon Radio frequency identification (RFID) is a radiosupported identification technology that typically operates by saving a serial number on a radio transponder that contains a microchip for data storage. Via radio waves, the coded information is communicated to a reading device (Jones et al., 2005). RFID does not represent a new development; it was devised by the American military in the 1940s. Since the technology’s clearance

for civil use in 1977, RFID has been successfully used for the identification of productive livestock, for electronic immobilizer systems in vehicles, or for the surveillance of building entrances (Srivastava, 2005). Due to decreasing unit costs (especially for passive transponders), RFID technologies now seem increasingly applicable for the labeling of goods and semi-finished products. By this, manual or semi-automatic data entry, for instance through the use of barcodes, can be avoided. This closes the technical gap

Copyright © 2010, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

RFID Technologies and Applications

between the real world (characterized by the lack of distribution transparency of its objects) and the digital world (characterized by logically and physically unambiguous and therefore distribution-transparent objects). In addition, RFID facilitates fully automated simultaneous recognition of more than one transponder without direct line of sight between reader and transponders.

execution system [MES], supply chain management [SCM], or e-commerce applications). The processor sends commands to the reader and receives its replies. The reader is connected to the processor through either a serial interface or a network connection. It contains a so-called “coupling unit,” which allows the reader to modulate coded commands onto a magnetic or electromagnetic alternating field. The size and form of this coupling unit may vary, and its dimension determines the design of the reader. The transponder has to be attached to the object to be identified. It is the actual information carrier. All transponders in the reader’s field receive commands and send back their response data. A transponder usually consists of a microchip and a coupling unit. There are various transponder designs; most common, however, are small spools attached to adhesive film.

2.

confIguratIon of rfId systeMs 3. A typical RFID system consists of three basic components (Jones et al., 2005): (1) a computer, (2) a reader, and (3) a transponder, as depicted in Figure 1. 1.

The computer runs an application that requires real world data (for instance enterprise resource planning [ERP], manufacturing

Figure 1. Logical RFID system architecture (Bitkom, 2005; Thiesse, 2005) Target application (1)

ERP

MES

Monitoring Middleware (5)

SCM

Reporting

Storage

Enterprise Application Integration

Events & Alerts Edgeware (4)

Command Tag business layer Data management layer Device management layer

Raw data RFID-Hardware

E-Commerce

Config. data

RFID devices: Transponder, reader, printer, sensors… Reader (2)

Transponder (3)

Reader

Transponder

Transponder

45

RFID Technologies and Applications

An application system that receives real world data through RFID technology has to take into account several factors for the processing of this data (Thiesse, 2005): it must be capable of filtering out erroneous messages; it needs to aggregate received data into complex events; it must support the syntactic and semantic transformation of received data and save it for analytical purposes. In addition to the three basic components, the RFID system’s technical architecture consists of two more elements (also see Figure 1): 4.

5.

RFID hardware has to contain control software that both transforms the raw data of radio communication into events compatible with the application and that reformats the application commands into data legible for the transponder. This type of software is referred to as “edgeware.” It controls the used data’s format and its tagging; it also monitors the connected RFID devices. Middleware systems pass on relevant events to the connected applications in the individual syntax and semantics. Middleware is mainly used for the simplification of configuration and for the alignment of RFID systems to the requests of various application fields and target applications.

technIcal standards for rfId systeMs Efforts to standardize systems on the basis of RFID technologies occur in three fields: standardization of transponder technology, of reader technology, and of RFID middleware. They are discussed consecutively in the following. First, transponder technologies can be classified using three criteria (Flörkemeier, 2005): according to the individual reading distance, there are close-coupling, remote-coupling, or long-range-coupling systems; according to the energy supply, there are passive, semi-active,

46

and active transponders; with respect to the storage structure there are so-called “writeonce/read-multiple” (WORM), read-write, and complex data structures. Unrelated to its reading distance, energy supply, and storage structure, a transponder usually saves at least one 96 bit (max) identification number (Flörkemeier, 2005). This identification number may be formatted according to the widely used number formats, for example, the universal product code (UPC), the European article number (EAN), or the serialized shipping container code (SSCC). The electronic product code (EPC) comprises a new development for RFID technology-based product identification. This code was specified by the Auto-ID Center (and its successor organization EPCglobal), a collaboration of producers and research facilities. In the future, several branches (not just retail) are to use EPC as a universal identification code for object identification (Bitkom, 2005). Four radio frequency bands are open for the radio transmission between transponders and readers worldwide: low frequency (LF), with a frequency band between 100-135 kHz; high frequency (HF), with a frequency band around 13.56 MHz; ultra high frequency (UHF), with a frequency band between 868-956 MHz; and the microwave range at 2.45 and 5.8 GHz. Ever since the first standardization of RFID technologies for the labeling of productive livestock in 1996 (ISO 11785) which used low frequency technology, both the International Organization for Standardization (ISO) and EPCglobal published several different system specifications concerning the four frequencies. LF and older HF systems make possible data transmission of 5 kbit/s and recognition rates of up to 10 transponders per second. Newer HF systems, however, allow for data transmission of 100 kbit/s and recognition rates of 30 (HF) or up to 500 (UHF) transponders per second. With regard to their configuration, there are four different types of readers: stationary gatereaders (used, for instance, at loading gates); compact readers and mobile readers, which

RFID Technologies and Applications

combine antennae and reading/writing appliances in compact, portable bodies; and vehicle-bound readers used solely stationary, for instance, in the cold room of a cooling transporter (Bitkom, 2005). EPCglobal specified a so-called readerinterface-protocol—an XML-based communication protocol—for the communication between the reader and the external target application (Flörkemeier, 2005). Third, RFID middleware is used for the data processing and aggregation into complex events, for the control and synchronization of these events, and for the simplified configuration of the RFID system for the target application (Bitkom, 2005). EPCglobal specified four technical components for the realization of RFID middleware systems (see Figure 2), which are described in more detail next: • Savant represents a normed interface between commercial RFID middleware and its target application. Savant is used for the

aggregation of RFID identification events into custom-designed events (e.g., converging a number of transponder identifications into the event of arrival of a single good). • The Physical Markup Language (PML) includes attributes of objects, processes, and environment. The PML Core vocabulary specifies the semantics for the exchange of context information on the basis of sensor data. PML Core is mainly used in connection with the reader-interface-protocol. • The EPC Information Service (EPC-IS) sends data to the individual transponderlabeled objects. The EPC-IS does not only use data sources of the individual RFID system, but can also access information of external sources. • The Object Naming Service (ONS) is a simple index service that is used for the translation of EPC object identifiers into customary Internet (DNS-) resource-addresses. The ONS receives the EPC from the reader,

Figure 2. Standard components of RFID middleware (Flörkemeier, 2005)

External software applications

Object Naming Service (ONS)

DNS Protokoll

PML EPC Information Service

PML

PML Savant Reader-interfaceprotocol & PML Core Reader

RFID transponder

RFID transponder

RFID protocols UHF Class 0/1 & HF Class 1

47

RFID Technologies and Applications

assigns it a specific EPC-URI, and translates this URI (Uniform Resource Identifier) into DNS-name.

applIcatIon fIelds for rfId technologIes RFID technologies permit the automatic identification of objects equipped with transponders. Transponders, which have sufficient storage capacities, make possible the object-linked transport of data about the object or about transport history. RFID technologies are useful in the electronic support of goods and turnover logistics. Potential areas of use of RFID in electronic logistics processes include the automatic processing of transport and transaction processes (especially for automatic stocking), the (semi)automatic decentral controlling of delivery chains (especially concerning goods traceability), the localization of object holders and containers, the control of production processes, as well as the configuration of security applications. In contrast to conventional identification strategies, RFID technologies offer four advantages (Strassner & Fleisch, 2005): the object identification does not rely on line of sight; several objects can be identified simultaneously (bulk reading); the data belonging to an object can be saved directly at the object (there is no need for a central database); and RFID transponders are generally more resistant than conventional identifiers (for example barcodes). The effects of RFID use in electronic logistics processes can be assessed from three different perspectives (Alt, 2004): • From the technical perspective, RFID transmits real time information, which is made available to all involved in these processes. On the other hand, the interface between operator and machine and between machine and machine has been improved. This enables a flow of information that is

48

free of disruption (EDI applications come to mind). The margin of error when entering and processing data is reduced. • With regard to the process, RFID decreases the margin for error for object identification and increases time and cost efficiency (including chaotic processes). On the one hand, fixed costs can be lowered. On the other hand, the economically reasonable information intensity can be increased with regard to the carrying out of processes (Lietke, 2005; Schumann & Diekmann, 2005). • From a strategic perspective, an increased object related information intensity enables a decrease in inter-company transaction costs and the creation of a basis for increased (and economically reasonable) independence between cooperating business partners. This produces potentials for outsourcing of tasks. Multilateral clearing-centers can be responsible for the accounts of services rendered. Taking the current development status of RFID technology into consideration, four problem areas exist (Mattern, 2005): bulk-reading, radio signal disruptions, transponder costs in open-loop systems, and safety concerns. Even if we want to bulk-read several transponders, these transponders need to be in close proximity to the reader because RFID technology operates from a distance of a few centimeters (passive transponder) to a few meters (active transponder). When identifying objects, errors can occur due to radio signal disruptions. Environmental factors (such as shadowing effects, reflections, etc.) or transponder effects are possible factors for radio signal disruptions. Cost-benefit relations appear unclear with regard to using the transponder to identify B- and C-goods/products. When marking single boxes or bulk (closed-loop product systems) that are reusable, the costs for the transponder are unproblematic because they can be used multiple times. Open-loop systems in which the transpon-

RFID Technologies and Applications

der is only used once are not as cost effective, and even the target cost of five U.S. cents per piece is too high (Tellkamp, 2005a). There are safety related concerns particularly with regard to unauthorized scanning of the data, unauthorized manipulation of data, or willful destruction of transponder data through mechanical, chemical, or electromagnetic forces (Srivastava, 2005). At this point in time, the usage of RFID technology is found in different applications, including using RFID technology in commerce, manufacturing industry, and service sectors. In the following, the potential as well as problems connected to using the RFID technology in these three areas will be clarified. In the area of commerce, RFID transponders offer a number of advantages particularly with respect to the placement of goods in the sales room (Tellkamp, 2005a): in real time, with the help of the automatic identification of goods, one can easily determine when stocks are running low on a particular product or whether there is a surplus of another product that has not been selling well. Additionally, in real time, RFID enables one to verify the target and actual deviation or rather the verification of stored goods, or the location of goods that are not at their designated place. Furthermore, RFID offers the potential of avoiding theft in the stores. Also, radio frequency identification tags with their stored data form the basis of improved consumer protection. The close adherence to protective regulations such as the continuous refrigeration of fresh produce can be controlled and proven through the supply chain (Thiesse, 2005). Because there is a lack of industry standards as well as a lack of complete solutions for RFID infrastructures, the diffusion of RFID technologies in retail businesses remains problematic. Moreover, the production costs of passive transponders are currently at 20 Euro cents and too expensive for smaller products in an open-loop system where transponders are not being re-used. Additionally, using the RFID

technology generates new and often unsolved challenges when coordinating the supply chain as well as questions concerning data protection. Pilot RFID projects include the cooperation between Kaufhof and Gerry Weber in the areas of logistics of clothes where production, storage/ distribution facility, and consumer market is concerned (Tellkamp, 2005b), the logistics of the retailer Wal Mart, or the so-called “Future Store” of the Metro AG. Because information availability is increased using the RFID technology, coordination costs are lowered for the manufacturing industry. Therefore, by employing procurement processes, a just-in-time production can target C-goods as well (Schumann & Diekmann, 2005). In the area of production planning and managing, we can abandon a complex (and therefore expensive) centralized planning in favor of a decentralized coordination when dealing with object-linked data transfer. Automatic blockage of stocks/goods in storage facilities and automatic order release for computer-controlled manufacturing sites are both examples of a decentralized coordination. Furthermore, the quality control of finished or semi-finished products can be relinquished to the buyer, and as a result liability risks decrease for businesses that further process the product. RFID systems are also used in the car industry, for example, BMW with its object accompanying transponders in the motor vehicle manufacturing process as well as VW with its radio supported object localization (Strassner & Fleisch, 2005). In the service sector, RFID technology is used to develop electronic or electronically supported admissions tickets. One well-known example for this development is the ticketing for the Soccer World Championship 2006 in Germany. Less prominent, but well established through daily usage, are RFID applications in the area of tourism such as radio supported ski passes or parking tickets. As opposed to conventional paper tickets, the RFID supported solution has a multitude of advantages (Flor, Niess, & Vogler, 2003):

49

RFID Technologies and Applications

• By distributing electronic tickets, the distribution logistics can be reduced significantly and in extreme cases becomes dispensable. • The seller of electronic tickets has the opportunity to decrease or end the distribution of tickets. • Electronic tickets can be made safe against counterfeit with the help of cryptographic techniques, electronically checked for their authenticity, and if lost, the tickets can easily be redistributed. Apart from being used for the distribution of tickets, RFID technology is also reviewed as a potential carrier of advertising information. For example, the Finnish cell phone manufacturer Nokia recently introduced a cell phone with an integrated reader. According to a showcase, the data for a song that was hidden within an advertisement could be downloaded (Nokia, 2004).

future challenges Even though RFID technology offers many opportunities to automate current processes and to generate new processes, the adaptation of this technology has evolved slower than anticipated by most supporters. The challenges that RFID technology faces are in the areas of technology, customer acceptance, and cost, as illustrated in the following. The technological challenges are particularly apparent in attempts to standardize the operation. Having clear technological standards, the smooth integration of RFID technology in existing systems would be enabled. In this context, particularly the multitude of used frequencies poses a problem. Due to this, so-called multimode readers that are capable of using different frequencies are growing in popularity (Garfinkel & Rosenberg, 2006). An additional challenge in the area of technology is the

50

processing of enormous amounts of data that are produced when using the RFID technology. There is a great need for efficient algorithms to analyze the data (Thiesse, 2005). Additionally, efficient encryption techniques have to be employed to protect the data so that it cannot be read by third parties (Spiekermann & Berthold, 2005). RFID technology is not as popular with customers as expected (Günther & Spiekermann, 2005). Mainly, this lack of acceptance is due to the following reasons: concerns over data protection, little knowledge about the technology used (Kern, 2006), and the fact that RFID is still in the early stages of innovation and thus not very developed. The existing technology (in this case the barcode) is seen as sufficient. Therefore customers typically remain skeptical of new radical technological innovations (Sheffi, 2004). Additional customer education and availability of information could increase customer acceptance of RFID technology (Boslau & Lietke, 2006). The cost of implementing RFID technology on a larger scale remains the most significant barrier for its usage (Thorndike & Kasch, 2004). The RFID transponders are the most expensive component in the development of the technology. EPCglobal is trying to work on this problem by seeking to reduce the costs of the transponders when developing a standard for RFID (low-cost RFID). Small transponders, easy data exchange protocols, and simple data structures are cornerstones of a strategy that enables RFID technology to be used more widely (Garfinkel & Rosenberg, 2006). However, the initial target of five cents per tag has not been realized so far. In this context, the polymer technology has come to our attention. In this case, RFID chips are not made from silicon anymore but from plastic. These polymeric tags can be directly stamped onto the product (Tellkamp, 2005a). RFID technology has not been proven to be economic, which poses another problem (Strassner, Plenge, & Stroh, 2005). Another question arises when looking at the value chain: how does one split the costs for this technology

RFID Technologies and Applications

Figure 3. Development trend for RFID technology use (Strassner & Fleisch, 2005)

Integration depth

Metro example

Products Integration depth Packages C resources B resources Carrier

VW example Closed systems

A resources Open systems

(Tellkamp, 2005a)? So far, the manufacturer was responsible for financing RFID transponders. However, the subsequent levels of the value chain profited the most from the technology (“essential paradox of RFID,” METRO Group, 2004, p. 26). Manufacturers of goods now have to make a decision as to how much they want to invest in this new technology in order to profit from it on the one hand and to satisfy the demands of retailers on the other (Thorndike & Kasch, 2004). Because “it is most likely that barcodes and RFID systems will coexist” (McFarlane & Sheffi, 2003, p. 5), a transitional period where both technologies are used has to be financed. Generally, there is a trend in the IT market that an increase in the depth of the integration (e.g., from A goods to C goods) supports an increase in the overall range of the integration (from single functions and departments to businesses and networks). RFID technologies not only promote this trend, but the development of RFID technology itself suggests this trend: with respect

Integration range

to the depth of the integration, one trend is that carriers (such as containers), single palettes, and the product itself are easily identifiable. When looking at the overall range of the integration, a trend that shows a move from closed to open systems can be identified. This trend seems to be dependent on the reduced prices for passive radio transponders (see Figure 3).

references Alt, R. (2004). E-Business und Logistik. In P. Klaus & W. Krieger (Eds.), Gabler Lexikon Logistik—Management logistischer Netzwerke und Flüsse. Retrieved September 28, 2006, from http:// www.alexandria.unisg.ch/publiscations/23760 Bitkom. (2005). RFID—Technologie, Systeme und Anwendungen (White Paper). Berlin: Bundesverband Informationswirtschaft, Telekommunikation und neue Medien e.V.

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Boslau, M., & Lietke, B. (2006). RFID is in the eye of the consumer—Survey results and implications. In N. Papadopoulos & C. Veloutsou (Eds.), Marketing from the trenches: Perspectives on the road ahead (pp. 1-18). Athens: Atiner. Flörkemeier, C. (2005). EPC-Technologie—vom Auto-ID center zu EPCglobal. In E. Fleisch & F. Mattern (Eds.), Das Internet der Dinge— Ubiquitous Computing und RFID in der Praxis (pp. 87-100). Berlin: Springer. Flor, T., Niess, W., & Vogler, G. (2003). RFID: The integration of contactless identification technology and mobile computing. In D. Jevtic & M. Mikuc (Ed.), Proceedings of the Seventh International Conference on Telecommunications ConTEL (Vol. 2, pp. 619-623). Piscataway: IEEE Press. Garfinkel, S., & Rosenberg, B. (2006). RFID applications, security, and privacy. Upper Saddle River, NJ: Addison-Wesley. Günther, O., & Spiekermann, S. (2005). RFID and the perception of control: The consumer’s view. Communications of the ACM, 48(9), 73-76. Jones, P., Clarke-Hill, C., Comfort, D., Hillier, D., & Shears, P. (2005). Radio frequency identification and food retailing in the UK. British Food Journal, 107(6), 356-360. Kern, C. (2006). Anwendung von RFID-systemen. Berlin: Springer. Lietke, B. (2005, May). Supply chain management in a new institutional framework. Paper presented at European School on New Institutional Economics (ESNIE), Cargèse, Corsica. McFarlane, D., & Sheffi, Y. (2003). The impact of automatic identification on supply chain operations. The International Journal of Logistics Management, 14(1), 1-18.

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METRO Group. (2004). RFID: Uncovering the value.RetrievedSeptember28,2006,fromhttp://cachewww.intel.com/cd/00/00/22/34/223431_223431. pdf Nokia. (2004). Nokia unveils the world’s first NFC product, Nokia NFC shell for Nokia 3220 phone. Retrived December 12, 2004, from http://press. nokia.com/PR/200411/966879_5.html Schumann, M., & Diekmann, T. (2005). Objektbegleitender datentransport entlang der industriellen wertschöpfungskette. In Arbeitsberichte der Abt. Wirtschaftsinformatik II, Georg-AugustUniversität Göttingen, No. 6. Sheffi, Y. (2004). RFID and the innovation cycle. The International Journal of Logistics Management, 15(1), 1-10. Spiekermann, S., & Berthold, O. (2005). Maintaining privacy in RFID enabled environments— Proposal for a disable-model. In P. Robinson, H. Vogt, & W. Wagealla (Eds.), Privacy, security and trust within the context of pervasive computing (pp. 137-146). New York: The Kluwer International Series in Engineering and Computer Science, Springer. Srivastava, L. (2005, April). Ubiquitous network societies: The case of radio frequency identification. Paper presented at ITU Workshop on Ubiquitous Network Societies, Geneva, Switzerland. Strassner, M., & Fleisch, E. (2005). Innovationspotenzial von RFID für das supply-chain-management. Wirtschaftsinformatik, 47(1), 45-54. Strassner, M., Plenge, C., & Stroh, S. (2005). Potenziale der RFID-Technologie für das Supply Chain Management in der Automobilindustrie. In E. Fleisch & F. Mattern (Eds.), Das Internet der Dinge—Ubiquitous Computing und RFID in der Praxis (pp. 177-196). Berlin: Springer.

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Tellkamp, C. (2005a). Automatische Produktidentifikation in der Supply Chain des Einzelhandels. In F. Mattern (Ed.), Total vernetzt. Szenarien einer informatisierten Welt (pp. 225-249). Berlin: Springer. Tellkamp, C. (2005b). Einsatz von RFID in der Bekleidungsindustrie. In F. Mattern (Ed.), Total vernetzt. Szenarien einer informatisierten Welt (pp. 143-159). Berlin: Springer. Thiesse, F. (2005). Architektur und Integration von RFID-systemen. In E. Fleisch & F. Mattern (Eds.), Das Internet der Dinge—Ubiquitous Computing und RFID in der praxis (pp. 101-117). Berlin: Springer. Thorndike, A., & Kasch, L. (2004). Radio Frequency Identification—RFID in Handel und Konsumgüterindustrie: Potenziale, Herausforderungen, Chancen. IM, 19(4), 31-36.

key terMs Bar Code: An automatic identification technology that encodes information into an array of adjacent varying width parallel rectangular bars and spaces, which are scanned by a laser. Coupling Unit: Allows the modulation of coded commands onto a magnetic or electromagnetic alternating field; can vary in size and form. Edgeware: Control software that transforms the raw data of radio communication into events compatible with the respective application and also reformats application commands into transponderlegible data.

Electronic Product Code (EPC): 64- or 96-bit code based on current numbering schemes (Global Trade Item Number [GTIN], etc.) containing a header to identify the length, type, structure, version, and generation of the EPC, the manager number, which identifies the company or company entity, the object class, similar to a stock keeping unit (SKU), and a serial number, which uniquely identifies a specific item of the object class. Middleware: Software residing on a server between readers and enterprise applications to filter data and pass on only useful information to applications. Some middleware is able to manage readers on a network. Radio Frequency Identification (RFID): A radio-supported identification technology typically operating by saving a serial number on a radio transponder that contains a microchip for data storage. Reader: Reading device or interrogator communicating with both the transponders (reading/ writing) and the external target application; format can be stationary (gate or vehicle-bound), compact, or mobile. Savant: Normed interface between commercial RFID middleware and its target application; used for aggregating RFID identification events into custom-designed events. Transponder: Mobile information carrier consisting of microchip, antenna, and coupling unit, which can be attached to an object and store data identifying the object or its (transport) history. Term originated from both transmitter and responder.

This work was previously published in Encyclopedia of Multimedia Technology and Networking, Second Edition, edited by M. Pagani, pp. 1232-1239, copyright 2009 by Information Science Reference (an imprint of IGI Global).

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54

Chapter 1.6

Understanding RFID (Radio Frequency Identification) Susan A. Vowels Washington College, USA

IntroductIon RFID, also known as radio frequency identification, is a form of Auto ID (automatic identification). Auto ID is defined as “the identification of an object with minimal human interaction” (Puckett, 1998). Auto ID has been in existence for some time; in fact, the bar code, the most ubiquitous form of Auto ID, celebrated its 30th year in commercial use in 2004 (Albright, 2004). Barcodes identify items through the encoding of data in various sized bars using a variety of symbologies, or coding methodologies. The most familiar type of barcode is the UPC, or universal product code, which provides manufacturer and product identification. While barcodes have proven to be very useful, and indeed, have become an accepted part of product usage and identity, there are limitations with the technology. Barcode scanners must have line of sight in order to read barcode labels. Label information can be easily compromised by dirt,

dust, or rips. Barcodes take up a considerable footprint on product labels. Even the newer barcode symbologies, such as 2D, or two-dimensional, which can store a significant amount of data in a very small space (“Two dimensional…,” 2005) remain problematic. RFID proponents argue that limitations of barcodes are overcome through the use of RFID labeling to identify objects.

hIstory of rfId Jeremy Landt (2001) wrote a history of RFID published by AIM, The Association for Automatic Identification and Data Capture Technologies, explaining that in the 20th century, the invention of radar took advantage of the electromagnetic energy that some postulate to have been present at the creation of the universe. By broadcasting and analyzing the reflection of radio waves, radar can identify two important characteristics about an

Copyright © 2010, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Understanding RFID (Radio Frequency Identification)

Figure 1. Barcode examples

object, its position and its velocity. This application of radio waves was a precursor to the use of radio waves in radio frequency identification. During the 1950s, transponders were developed and improved, becoming increasingly more sophisticated and allowing for long-range determination of the identification of aircraft (Landt, 2001). Through the decades of the 1960s, 1970s, and 1980s, inventors, academicians, commercial enterprises, and governmental agencies explored a plethora of opportunities related to the use of early RFID devices, using radio transmissions, “shortrange radio-telemetry,” microwave technology, and radar beams (Landt, 2001). Landt states that RFID was first used commercially in the 1960s by companies that developed security related devices called “electronic article surveillance (EAS) equipment.” Although EAS could only present the detection or absence of a tag, the tags were low cost and provided valuable deterrents to theft. EAS is still an important application of RFID today. Work continued through the 1970s and in the 1980s, as companies began offering a variety of RFID related business solutions, primarily aimed at transportation, controlled access, and animal tracking applications (Landt, 2001). Of primary importance, in 1973 the United States government determined that there was no need for a national standard for electronic vehicle identification. This was serendipitous because it meant that individual firms, researchers, and others could

have the freedom to develop new uses of RFID without being constrained by a governing body (Landt, 2001).

rfId technology radio frequency Electromagnetic waves are comprised of a continuum of emanations, including visible light waves, and invisible frequencies such as television and radio waves, which are lower frequency than light, and x-rays and gamma rays, which are higher frequency than light. Frequencies are measured in Hertz (Hz), kilohertz (kHz), megahertz (MHz), or gigahertz (GHz), and represent the rate of oscillation of the waves. The portion of the electromagnetic spectrum used by radio frequency identification includes LF (low frequency), HF (high frequency), and UHF (ultra high frequency), which are all portions of the radio wave frequency bands, hence the term “radio frequency identification.” An advantage of radio waves over visible light is that radio waves can penetrate many substances that would block visible light. Radio waves range from 300 kHz to 3 GHz (Hodges et al, 2003). Specific frequencies use is controlled by governmental agencies. Some of the concerns relating to RFID are inherent to the technology upon which it is based. For instance, the range over which devices using

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Understanding RFID (Radio Frequency Identification)

radio waves can consistently communicate is affected by the following factors: 1.

The power contained in the wave transmitted The sensitivity of the receiving equipment The environment through which the wave travels The presence of interference (Hodges et al., 2003)

2. 3. 4.

Hardware Components The radio frequency transmissions in RFID travel between the two primary components, the RFID reader and the RFID tag. The reader can be mobile or stationary and is the proactive component. It consists of an antenna and a transceiver, is supplied with power, and generates and transmits a signal from its antenna to the tag and then reads the information reflected from the tag (Hodges et al., 2003). The antenna is used to send and receive signals; the transceiver is used to control and interpret the signals sent and received (“What is…,” 2005). The tag, a transponder, is affixed to the object being identified, such as an automobile, a shipping pallet, or a tagged marine mammal. Thus, we can see a major benefit in using RFID since the data is exchanged using radio waves; it is not necessary to have line of sight between a reader and a tag, such as is required with barcodes.

This permits a great deal more flexibility in the use of the RFID. Although all readers have an external power source, tags may be completely without power or with some degree of power, and fall into three categories1: (1) Passive tags are inert; they do not have any power source and must use energy from the radio wave that is transmitted from the reader. This reduces the costs of the tags, but also reduces their performance. (2) Semi-active tags incorporate a battery which powers the electronic circuitry while the tag is communicating with a reader. Although the power is not used to produce radio waves, the power source improves the performance of the tag, most commonly by increasing the transmission range. (3) Active tags are fully powered by battery; they are able to generate radio waves autonomously, without the need for a reader to first transmit a radio wave. As power sources are added to these tags, we can see that their utility increases, but at the expense of the cost per tag, and so active and semipassive tags are generally reserved for higher-value items (Angeles, 2005; Hodges et al., 2003). The tags consist of three components: antenna, silicon chip, and substrate or encapsulation material (Want, 2004). The antenna is used for receiving and transmitting radio frequency waves to and from the reader. The chip contains information pertaining to the item tagged such as part number and manufacturer. Chips can be either read-only or read-write; the costs are higher

Figure 2. The electromagnetic spectrum (Adapted from Hodges, 2003) TV FM Radio

AM Radio LF

MF

HF

Low frequency Long wavelength

56

VHF

Microwaves FM Radar UHF

Infrared

Visible Light

Ultraviolet

X-rays; Gamma Rays High frequency Short wavelength

Understanding RFID (Radio Frequency Identification)

Figure 3.

SAMPLE PAPER LABEL WITH EMBEDDED RFID TAG (Source: http://www.suppliersystems.com/rfid.htm)

RFID TAG MICROCHIP ANTENNA (headings supplied by author)

for the read-write chips. There is a crucial difference between read-only chips and read-write chips. Read-only chips are essentially electronic barcodes. Once the data has been encoded onto the chip, it cannot be modified and, therefore, cannot transmit information about the product as it moves through a sequence of events (“The Write Stuff…,” 2003). A twist on the read-only vs. read-write chips is the EEPROM (electrically erasable programmable read-only memory chip). While individual pieces of information on EEPROM chips cannot be modified, the entire existing data on these chips can be replaced by new data (Angeles, 2005; Want, 2004).

ated through RFID. Traditional barcodes require just the addition of the UPC code to the existing database of items. RFID, by virtue of its use of a computer chip, has the capability of not only storing static data, such as UPC codes, but also of storing dynamically created information, such as movement of the product through a supply chain. Early adopters of RFID are using current database and application systems and modifying them to accommodate the currently modest amount of additional data. However, the industry understands that RFID technology brings with it the promise of huge amounts of data to be managed, stored, and communicated.

software rfId standards The RFID reader and tags represent just part of the entire RFID story. RFID is feasible only due to advances in database management and information technology which have allowed the storing, processing, and analysis of the data gener-

electronic product codes Just as barcodes encoded universal product codes, RFID tags encode electronic product codes,

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Understanding RFID (Radio Frequency Identification)

known as EPCs. The EPC is a unique standard in that it is being systematically developed well in advance of its use rather than being cobbled together on the fly as has happened with other standards. The Auto-ID Center at MIT began the thought process to develop EPC. The original concept was that using RFID and EPC would permit an “Internet of things,” a universe of identified objects that could be tracked, interrogated, and provide added value to supply chains by enabling granular information at the item level for every item, big or small, high value or low value (“EPC: The End of Bar Codes?,” 2003). The Auto-ID Center has completed its pioneering work and passed the torch on to EPCGlobal. The labs of the Auto-ID Center are still in existence under the aegis of Auto-ID Labs (www.autoidcenter.org). EPCGlobal’s focus is not only on the creation of EPC standards, but also on the creation of a global community of EPC users spanning a multiplicity of supply chains around the world (“RFID Implementation Cookbook,” 2006).

frequency allocations The frequencies used by RFID devices are dictated by the governments of the countries in which the technology is deployed. The management and allocation of specific frequencies for use by commercial and governmental agencies has been seen as a responsibility which should devolve to the government to control. As an example, Hall and Schou (1982) argued that what they called the electromagnetic spectrum was essentially a finite resource with strategic importance to national and international communication and to the national economy. With respect to RFID frequency allocations, governments are beginning to realize that it is also important to “harmonize radio communication systems” with other countries in order to benefit most fully from international trade. Developers and users of RFID need to become familiar with the legislation pertaining to RFID for their

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areas. It should be noted that even if there are conflicting frequencies assigned, in some cases it is possible for developers to obtain waivers to test RFID systems outside of assigned spectrums if the system being created is intended for use in another country (Hodges, 2003).

governing bodies/testing and research facilities Two primary governing bodies are involved with development of RFID standards. As mentioned earlier, EPCGlobal has taken up the development of standards from the Auto-ID Center. In addition, AIM Global (the Association for Automatic Identification and Mobility) is working with CompTIA, the Computing Technology Industry Association to develop an RFID certification that will be vendor-neutral and cover such items as “radio frequencies, interference, terminology, and standards” (“CompTIA…,” 2005). Independent testing and research facilities are also moving along the development of RFID technology. Examples include the nonprofit RFID Alliance Lab, based at the University of Kansas (Swedberg, 2006) and the University of Arkansas’ RFID Research Center (“Researcher…,” 2006).

Technology Development Current research is concentrating on tags that are not affected by liquids or metals, and that permit the reading of closely packed tags such as would be used when tagging individual items in a retail situation. Early testing has indicated that Generation 2, known as Gen 2, UHF tags successfully fill these criteria. UHF, or ultra high frequency, permits near-field reading, in which the reader is close to the tag being read, in addition to far-field reading of tags. When transmitting in a near-field situation, the UHF tags transmit through the magnetic field; when transmitting in a far-field situation, the UHF tags transmit through the electromagnetic field. However, others, par-

Understanding RFID (Radio Frequency Identification)

ticularly in the pharmaceutical industry, believe that HF, high frequency, tags are more efficient. The possibility of multiple standards looms as a concern for companies involved in multiple industry sectors (O’Connor, 2006).

rfId successes Transportation Industry EZPASS is a well-known and well-accepted area of RFID technology use deployed in the eastern part of the United States. The EZPASS system was developed for a consortium of states wishing to automate the toll-collecting process on major highways, tunnels, and bridges. With the EZPASS system, motorists are issued a transponder which can be mounting on the inside of the front windshield. When the vehicle passes an EZPASS toll collection point, a stationary reader recognizes the serial number encoded in the transponder. This serial number is used to identify the motorist’s EZPASS account, in which funds are held in escrow. The amount of the toll is automatically deducted from the fund. When the fund balance falls below a minimum amount, it is automatically replenished by charging a credit card account furnished by the motorist. Initially, motorists were induced to participate through discounts offered on tolls collected by EZPASS vs. tolls collected manually. EZPASS has reduced the number of toll takers and, in some instances, increased the throughput of vehicle traffic by allowing drivers to pass the toll collection station at speed. Although the transponders are bulky, they are easily mounted. While there is no charge for the transponders, motorists are responsible to return them when leaving the program; unreturned transponders are subject to a fee (Vavra et al., 1999).2

Supply Chains Supply chains consist of manufacturers and retailers working together to provide product to the end consumer. Supply chain partners rely on close working relationships in order to increase the efficiency and lower the costs of moving product from the raw material stage through manufacturing to the final retailing of the merchandise. RFID is proving to be a valuable tool to this end. Wal-Mart Corporation has been a major force in the deployment of RFID within supply chains. In 2003, Wal-Mart dictated that its top 100 suppliers must implement RFID to identify cases and pallets being shipped through the Wal-Mart distribution system by 2005 (Seideman, 2003). Early examination of the impact has shown that RFID has reduced Wal-Mart’s replenishment cycle and increased inventory accuracy (“Study of Wal-Mart…,” 2004). Another retailer that has made significant contributions to the evaluation of RFID is Metro Group, a German supermarket firm. In its Future Store near Dusseldorf, Metro Group has tested products ranging from razor blades to cream cheese (Tarnowski, 2005). Marks and Spencer, a clothing retailer in the United Kingdom, has been successful in using RFID garment-tagging to increase its inventory accuracy (“Marks & Spencer,” 2005).

Other Applications RFID has already proven to be a valuable technology in a number of industries. Some other applications include asset tracking, condition monitoring, and fleet management. The mining industry was an early adopter of RFID technology. One use of RFID tags in mining was in validating the correct movement of haulage vehicles. These vehicles have read only tags permanently attached to the vehicles dump bed. As a vehicle approaches a dump area, a reader validates that it is approaching the correct dump

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Understanding RFID (Radio Frequency Identification)

bed. Information concerning the transaction, including the vehicle number, the weight of the vehicle before and after the dump, and the time, are recorded automatically. Using RFID obviates the need for human interaction between the scales operator and the vehicle driver (Puckett, 1998). Asset tracking is an important application for RFID. Scottish Courage, a major UK brewer, used RFID to track beer kegs. In the brewing industry, reusable beer kegs constitute a major expense; when kegs are lost or not returned, these costs escalate. By tagging kegs with RFID labels, Scottish Courage was able to cut its keg losses in half, defer the need for purchase of new containers, and improve the visibility of the kegs and products (Wilding, 2004). Because the chips embedded in RFID tags can record environmental information, RFID is very useful in monitoring the condition of tagged items. The United States military uses this feature to monitor the physical condition of munitions, which are very sensitive to heat, humidity, and physical shocks (IDTech Ex Ltd, 2003).

rfId concerns technical Issues RFID users have encountered limitations with its usage. Liquids and metals impede the transmission of radio frequency waves (Leach, 2004). These materials, known as dielectrics, cannot conduct electricity (O’Connor, 2006). Another technical issue concerns the possibilities of collisions. Collisions can occur in two ways. First, if two readers are in close physical proximity, their signals can overlap and interfere with each other. Second, if tags are in close proximity to each other, a similar collision problem can arise. Anticollision schemes to address the first problem include programming readers not to read tags at the same time and setting up an additional system to delete duplicate codes. The

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second problem can be addressed by setting up a query and response requirement between tag and reader that will only permit a matching condition to proceed (Angeles, 2005).

privacy Issues A major concern surrounding RFID is a potential loss of privacy on the part of consumers who purchase items which have been tagged using RFID technology. Consumer privacy advocates question the possibility of firms being able to track consumers by the RFID tags embedded in clothing. This concern has led the EPC to dictate that tags must be equipped, at a minimum, with at least one method for nullifying the transmission of data (Ohkubo et al., 2005). It has been noted that the adoption of item-level tagging in retail supply chains has been slowed at least in part by this privacy concern.

conclusIon RFID is a very exciting technology with huge potential in many applications. As the technology’s cost decreases and it becomes more efficient, the use of RFID is expected to grow exponentially. With that growth, important questions need to be answered to address privacy and other social concerns about the information being provided by these very smart chips.

references Albright, B. (2004). The UPC Turns 30. Frontline Solutions. Vol. 5 Issue 9 (pp. 44-48). Angeles, R. (2005). RFID Technologies: SupplyChain Applications and Implementation Issues. Information Systems Management. Vol. 22 Issue 1 (pp. 51-65).

Understanding RFID (Radio Frequency Identification)

“Automated Order Filling & Warehouse Management Systems from Supplier Systems Corporation,” Supplier Systems Corporation. Retrieved December 17, 2006, from http://www.suppliersystems.com/rfid.htm “Barcode Label Printing Software – Barcode Creator,” Naxter, Inc. Retrieved December 17, 2006, from http://www.naxter.com/format.htm

www.aimglobal.org/technologies/rfid/resources/ shrouds_of _time.pdf Leach, P. T., (2004). Ready for RFID? The Journal of Commerce, Vol. 5 Issue 42 (pp. 12-14). Marks & Spencer Expands RFID Trial, (April 2005). Frontline Solutions, Vol. 6 Issue 3 (pp.1112).

“CompTIA and AIM to Develop RFID Certification,” (2005). Certification Magazine, Volume 7 Issue 2 (pp. 10-10).

O’Connor, M. C. (2006). Wal-Mart Seeks UHF for Item-Level. RFID Journal, Mar. 30, 2006. Retrieved on March 31, 2006 from http://www. rfidjournal.com/article/articleprint/2228/-1/1/

EPC: The End of Bar Codes?, (2003) The Association for Automatic Identification and Mobility, Retrieved December 17, 2006, from http:// www.aimglobal.org/technologies/rfid/resource/ articles/April03/EPCpart1.htm

Ohkubo, M., Suzuki, K. & Kinoshita, S. (2005). RFID Privacy Issues and Technical Challenges. Communications of the ACM, Vol. 48 Issue 9 (pp. 66-71).

“Free Barcode Font Code 39 TrueType Download,” ID Automation.com. Retrieved on April 30, 2006 from http://www.idautomation.com/fonts/free/ Hall, C. & Schou, K. (1982). Management of the Radio Frequency Spectrum in Australia. Australian Journal of Management. Volume 7 Issue 2 (pp. 103-116). Hodges, S. & Harrison, M. (2003). Demystifying RFID: Principles & Practicalities. Cambridge, United Kingdom: Auto-ID Centre, Institute for Manufacturing, University of Cambridge. Retrieved March 5, 2006, from http://www.autoidlabs.org/whitepapers/cam-autoid-wh024.pdf Holmes, T. J. (2001). Bar Codes Lead to Frequent Deliveries and Superstores. The RAND Journal of Economics. Vol. 32 Issue 4 (pp. 708-725). IDTech Ex Ltd, (2003). Smart Labels USA 2003 Conference Review, Smart Label Analyst, Issue 27, April 2003 Landt, J. (2001). Shrouds of Time: The history of RFID. Pittsburgh, USA: The Association for Automatic Identification and Data Capture Technologies. Retrieved March 4, 2006, from http://

Puckett, D & Patrick, C. (1998). Automatic Identification in mining. Mining Engineering. Vol. 50 Issue 6 (pp. 95-100). Researcher to Reveal EPC’s Further Impact at Wal-Mart (2006). RFID Journal, March 27, 2006. Retrieved March 31, 2006, from http://www.rfidjournal.com/article/articleprint/2221/-1/1 “RFID Implementation Cookbook (2nd Release – Sept. 2006),” (2006). EPCGlobal. Retrieved December 17, 2006, from http://www.epcglobalinc. org/what/cookbook/ Seideman, T. (December 1, 2003). The race for RFID, The Journal of Commerce, Vol. 4 Issue 48 (pp.16-18). Study of Wal-Mart reveals first benefits of RFID, (December 2004). Healthcare Purchasing News, Vol. 29 Issue 12 (pp. 6). Swedberg, C. (2006). University of Kansas’ Tag for Metal, Liquids. RFID Journal, April 19, 2006. Retrieved April 22, 2006, from http://www.rfidjournal.com/article/articleprint/2275/-1/1

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Tarnowski, J. & Longo, D. (2005). RFID driving future of tech, Progressive Grocer, Vol. 84 Issue 3 (pp.7-9). The Write Stuff: Understanding the Value of Read/Write RFID Functionality (2003). Intermec. Retrieved March 4, 2006, from http://www.aimglobal.org/technologies/rfid/resources/RFID%20 Read%20write%20WhitePaper.pdf Two dimensional (2D) Bar Code Symbologies (2005). Association for Automatic Identification and Mobility. Retrieved December 27, 2005, from http://www.aimglobal.org/technologies/ barcode/2d_symbologies.asp Understanding Gen 2: Key benefits and criteria for vendor assessment. Symbol White Paper. Retrieved March 7, 2006, from http://promo.symbol. com/forms/gen2/RFID_WP_0106_ final.pdf Vavra, T. C.; Green, P. E.: Krieger, A. M., (1999). Evaluating EZPass. Marketing Research. Vol. 11 Issue 2 (pp. 4-16). Want, R. (2004). The Magic of RFID. ACM Queue. Vol. 2 Issue 7 (pp. 40-48). What is Radio Frequency Identification (RFID)? (2005). Association for Automatic Identification and Mobility. Retrieved December 27, 2005, from http://www.aimglobal.org/technologies/rfid/ what_is_rfid.asp Wilding, R. & Delgado, T. (2004). RFID Demystified: Supply-Chain Applications. Logistics & Transport Focus. Vol. 6 Issue 4 (pp. 42-48). www.autoidcenter.org, Retrieved on March 5, 2006, at http://www.autoidcenter.org

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other resources

www.aimglobal.org www.autoidlabs.org www.epcglobalinc.org

key terMs Active Tag: Type of RFID tag that contains a battery power source that is used for all of its functioning. Active tags can autonomously produce radio waves without the presence of a reader. Air Interface: Air, the medium through which radio waves are transmitted. Alignment: How the reader is oriented to the tag. Auto ID: Auto ID, also called “Automatic Identification,” is a form of ICT that enables identifying information about objects to be gathered through the agency of scanners and readers. Auto ID encompasses barcodes, RFID, and similar tagging technology which can be read and interpreted automatically by a mechanical device. A bar code reader can interpret a printed bar code; an RFID reader can interpret an RFID tag. Bar Code: Automatic identification technology that generally employs a series of black vertical bars separated by vertical white spaces as a method of encoding numeric and alphanumeric data. Commonly used forms of barcodes are placed on consumer goods to identify universal product codes (UPCs). Newer technologies of barcodes include 2D (two dimensional) which allow more information to be encoded using a smaller area. There must be a line of sight between barcodes and barcode scanners in order for information to be read.

Understanding RFID (Radio Frequency Identification)

Dielectrics: Materials, such as liquids, that are not able to conduct electricity. These materials interfere with the transmission of radio frequency waves. EAN (13-digit UPC code): Provides more flexibility than original UPC code. EAS (Electronic Article Surveillance): The use of an RFID tag to identify valuable property in order to reduce theft. EDI (Electronic Data Interchange): The electronic transmission of business information from one supply chain member to another, using a standard data format and standard transaction codes. An EDI transaction, known as Advance Shipment Notice, or ASN, is being coordinated with data tracked by RFID tags on products moving through supply chains. EPC (Electronic Product Code): Encoded on RFID tags and tied to a multiplicity of data concerning the object tagged. Standards are still being developed and proposed for EPC by EPCGlobal, an international organization devoted to creating a community of supply chain firms cooperating to consistent end-to-end partnerships of product movement and tracking. Frequency: Frequencies constitute the rate at which electromagnetic waves, such as light, television, and radio waves, oscillate. Electromagnetic waves are comprised of a continuum of emanations, including light waves which are visible, and invisible frequencies such as television and radio waves which are lower frequency than light, and x-rays and gamma rays which are higher frequency. Frequencies are measured in Hertz (Hz), kilohertz (kHz), megahertz (MHz), or gigahertz (GHz), and represent the rate of oscillation of the waves. Gen 2: Second generation tags. Uses ultra high frequency range of radio waves.

HF (High Frequency): The original range of frequencies used with case and pallet level tagging in supply chains. The signals exchanged between HF tags and readers are subject to attenuation due to dielectrics. Passive Tag: Type of RFID tag that does not have a battery incorporated and therefore must rely on power contained in the radio wave transmitted by the reader. Passive tags are the lowest cost tags, but also perform at the lowest level. Reader: One of the two components of an RFID system. The reader generates and sends a radio wave signal to the tag, and captures and decodes the reflected signal from the tag in order to identify the object to which the tag is attached. All readers have some power source. Also known as an interrogator. RFID: RFID, or radio frequency identification, is a form of Auto ID in which radio waves are used to gather information from electronic tags attached to items such as vehicles, merchandise, or animals. Semi-active Tag: Type of RFID tag with a built-in battery power source which provides power to the electronic circuitry while the tag is communicating with the reader. Semi-active tags do not have enough power to autonomously generate radio waves. Tag: One of the two components of an RFID system. The tag, a radio frequency transponder, is affixed to the product that needs to be identified and is actuated by receiving a radio wave sent to it by the reader. See passive tag, semi-active tag, and active tag. Transceiver: An electronic device which is both a TRANSmitter and a reCEIVER. Transponder: Also known as a tag, a transponder electronically TRANSmits and resPONDs.

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Understanding RFID (Radio Frequency Identification)

UHF (Ultra High Frequency): UHF is being tested with Gen 2 chips as a means of overcoming problems with RF tags because the UHF emanations are not affected by dielectric materials in the same way in which RF is affected. UPC (Universal Product Code): UPCs are used to identify consumer goods and consist of a manufacturer’s number combined with a product number. The manufacturer’s identification number is assigned by the Uniform Code Council; the manufacturer can then assign its own product number.

endnotes 1

2

Some sources simplify the types of tags into two categories: active and passive. See “What is Radio Frequency Identification (RFID)?, 2005 Information also based on the author’s personal experience with EZPass.

This work was previously published in Encyclopedia of Information Communication Technology, edited by A. Cartelli & M. Palma, pp. 782-790, copyright 2009 by Information Science Reference (an imprint of IGI Global).

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Chapter 1.7

Radio Frequency Identification History and Development Chin-Boo Soon The University of Auckland, New Zealand

abstract

IntroductIon

This chapter describes the history and development of Radio Frequency Identification (RFID). Key information on RFID such as the ratification of the RFID standards and important regulations on frequency usage is presented. As businesses move towards the convergence of information, RFID technology provides a step closer to the reality of connecting the real world and the digital world seamlessly. This is possible as RFID communication does not require the line of sight as barcodes do. Thus, is the continued existence of the barcodes technology under threat? Before RFID makes its way into the mainstream, there are teething issues to be sorted out. The immediate attention for a global uptake of RFID is the adoption of a frequency standard that is accepted internationally. This chapter provides an understanding of the RFID technology, its background and its origin

Radio Frequency Identification (RFID) is an Automatic Identification and Data Capture (AIDC) technology. Its application can be found in most industries, offices and even homes. The application ranges from electronic article surveillance (EAS) in retails, electronic toll collection in transportations, to building access control in offices. RFID is fundamentally a radio technology and its history can be traced back to the 1930s (Bhuptani & Moradpour, 2005). The underlying principle of RFID is the transmitting and receiving of data in a form of electromagnetic energy. The primary components are tags and readers. Together these components form a coupling relationship where communication becomes possible. This chapter revisits the history of RFID development and looks at other forms of AIDC. This helps to form an epistemology of what RFID is and its origin, so that we could relate to the various aspects of RFID characteristics when planning on a RFID

Copyright © 2010, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Radio Frequency Identification History and Development

project. The emergence of RFID has raised the question of barcodes’ continued existence (Allen, 1991; Atkinson, 2004). It is therefore inevitable to know the characteristics of RFID and barcodes, and examine their future existence, particularly in the supply chain. The discussion in this chapter is motivated by the activities of RFID surrounding supply chain management. The suppliers’ mandates to use RFID in the supply chains have significant impact on businesses (C. B. Soon & J. A. Gutierrez, 2008). This has created interest in RFID by businesses around the world. It is thus an appropriate topic to introduce RFID. Although this chapter is focused on RFID applications in the supply chains, the technical aspects are common across application areas. This chapter is arranged as follows. First, the development of RFID is summarised with key events identified from the history of RFID. Second, the various concepts of AIDC are discussed. Third, the RFID system is discussed with particular attention to the tag classification and frequency allocation. Fourth, a comparison between RFID and barcodes is made. The continued existence of barcodes and the future of RFID are discussed in the conclusion.

hIstory: the developMent of rfId Electromagnetic theory was developed in the 1800s. Michael Faraday discovered that light and radio waves are part of electromagnetic energy and James Clerk Maxwell demonstrated that electric and magnetic energy travel at the speed of light in transverse waves (Landt, 2001). The discovery led to consequential experiments. In 1896, Guglielmo Marconi successfully transmitted radio waves across the Atlantic (Landt, 2001). Marconi’s demonstration was followed by more innovations. In 1922, radar was developed. The

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transponder (or tag) and interrogator (or reader) were then bulky and heavy. Radar was extensively used by the Allies during World War II to identify friendly military aircraft. Radar was further developed into a commercial air traffic control system in the late 1950s following the invention of integrated circuits (IC), which greatly reduced the size of RFID components. The 1960s marked the start of RFID development as scientists and commercial businesses started to show interest in the technology. The first concept of RFID for commercial use was probably thought of by Mario Cardullo in 1969 when he worked with an IBM engineer on a car tracking system using barcodes for the railroad industry (Shepard, 2005). Most RFID applications were identified in the 1970s. The use of RFID for EAS began in early 1970s (Bhuptani & Moradpour, 2005). EAS is a simple anti-theft measure for use in retail stores. It is the first and most widely used RFID application commercially (Landt, 2001). Further interest in the adoption of RFID extended to areas such as vehicle tracking, access control, animal tagging, and factory automation. The use of RFID cards for controlling access to office building by Westinghouse (Mullen & Moore, 2005) is an example of access control. Further development improved the reading speed and enabled a longer read range. The advanced RFID systems were utilised to identify railroad cars and track animals in the 1980s, and for electronic toll collection in the 1990s (Bhuptani & Moradpour, 2005). RFID applications became more widespread in the 1990s. The success of electronic toll collection kicked off large scale deployments throughout the United States, Europe and Asia (Landt, 2001). There are two basic systems employed in road toll collection. One uses a contactless card or proximity card and the other uses a transponder fitted into the vehicle. The latter does not require the vehicle to halt at a barrier unlike the proximity card model where, the driver has to stop and hold the proximity card close to a reader at the bar-

Radio Frequency Identification History and Development

rier or toll plaza. Standards for contactless smart cards were developed between 1992 and 1995. Contactless smart cards are now widely used in retail electronic payment, access control, transport fare payment, and airlines ticketing. It is not until late 1999 that RFID made its way into supply chains. Sanjay Sarma, a professor at MIT, started a project called the Distributed Intelligent Systems Center to work on ubiquitous object identification (Sarma, 2005). The centre also developed Electronic Product Code (EPC), Object Naming Service (ONS), Physical Markup Language (PML), and the Savant system. Together these components form the fundamental mechanism in the RFID system known as the EPC network. Sarma and his team developed a microwave prototype installed with a RFID reader. The reader read the tag information on a packet food, retrieved the cooking instructions from a server using the tag identity or EPC, and started cooking with the downloaded instructions. Having

successfully demonstrated the EPC concept using the microwave prototype, Sarma and his team were eager to secure commercial support as well as sponsorships to further develop the technology. After some convincing selling, they finally launched the Auto-ID Center with sponsorship from Gillette and Procter & Gamble on September 30, 1999 (Sarma, 2005). The Center continued its research work, and by 2003 there were six laboratories and more than a hundred sponsors. The increasing demand and interest triggered the Auto-ID Center to spin-out and hence EPCglobal was formed. EPCglobal is a not-for-profit organization jointly administered by Uniform Code Council (UCC) and European Article Numbering (EAN) International, or GS11. Under the GS1 umbrella, EPCglobal’s membership now reaches the entire globe with more than 100 member organizations (Smucker, 2006). A turning point for RFID in supply chain (RFID/SC) widespread use came when WalMart joined the Auto-ID Center in 2001 (Sarma,

Figure 1. The history of RFID 1800s Fundamentals of EM

1922 Radar invented

1896 Radio invented

1970 EAS in use

1960s Research on RFID in laboratory

1958 IC developed

1937 IFF System used in WWII

1980s GM use RFID for commercial purposes Railroad in US Farm animal in Europe

1972 Access control in use UPC developed

1950s Commercial air traffic control system

1999 MIT Auto-ID Center formed EPC developed

1992 - 1995 Contactless Smartcard standard developed

1969 First RFID concept developed

2002 Gillette order 500 million tags 2006

2001 Wal-Mart joined Auto-ID

2003 EPCglobal formed

1990 Toll collection

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Radio Frequency Identification History and Development

2005). A major field trial was conducted which involved forty companies across eight states and ten cities in the United States. The trial was not only successful, it demonstrated the practicality of RFID/SC and its economic benefits. This prompted Gillette to order 500 million tags in late 2002 and Wal-Mart to announce the mandate for its suppliers in 2003. Both events proved to be the catalysts of RFID/SC adoption. Figure 1 shows the development of RFID described above in a time chart. Other recent RFID applications are location sensing or real-time locating systems (RTLS), content management, electronic pedigree (epedigree), and in the sports for time tracking. The use of RFID for location sensing applications has some successful implementation such as the WhereNet RTLS infrastructure used to track shipping containers at APL terminals (Violino, 2006). Other location sensing innovation using radios includes LANDMARC (Ni, Liu, Lau, & Patil, 2004), RADAR (Bahl & Padmanabhan, 2000), and SpotON (Hightower, Vakili, Borriello, & Want, 2001). The use of RFID for content management includes authenticating and monitoring the content of a desired inventory. Examples of such applications are the e-pedigree used in the healthcare industry (Swedberg, 2008b) and tanker monitoring systems used by petroleum company to ensure the correct type of oil is delivered (Swedberg, 2008a). The use of RFID in the sport arena has several applications such as ticketing and recording the lap time of the NASCAR races (Edwards, 2008).

autoMatIc IdentIfIcatIon and data capture (aIdc) This section describes the various concepts of AIDC and traces the historical context of these technologies in the attempt to draw comparisons to RFID and put in perspective the development

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of RFID technology. AIDC is a collective of technologies that capture or collect data using automated mechanism without the need for manual input. Finkenzeller (2003) highlights five types of AIDC systems; (1) Barcode, (2) Optical Character Recognition, (3) Biometric, (4) Smart Card, and (5) RFID. Figure 2 illustrates his AIDC diagram. Magnetic Stripe and Magnetic Ink Character Recognition (Mullen & Moore, 2005) has been added to the diagram to illustrate AIDC more fully. The barcode, magnetic stripe, and RFID technologies emerged between the 1930s and the 1940s. Barcode was first patented in 1949 to Norman Woodland and Bernard Silver (Shepard, 2005). Woodland used ancient movie soundtrack encoding schemes and the dot and dash patterns in Morse code to create the first barcode. He extended the dots and dashes vertically to form linear pattern of thick and thin lines. He later realised that the linear pattern had to be scanned from a particular direction. Woodland replaced the linear pattern with a circular centric pattern resembling a bull’s-eye. This design could be read generally from any direction. However, the machine he designed to read the barcode was huge and therefore was not suitable for grocery checkout as it was originally intended. Nevertheless, it did find its way to tracking rail cars on the United States national railroad system in the late 1960s after some modification to the barcode pattern. Meanwhile, barcodes continued to evolve around the grocery industry in the United States. The bull’s-eye system was eventually replaced by the Universal Product Code (UPC) due to the difficulty of printing concentric circles on products. As such, linear barcode was adopted as it was easily printed, and with advanced scanner using laser technology, the linear barcode can be read from different angles. UPC was adopted on April 3, 1973 (Shepard, 2005), and was first scanned in commercial transactions in 1974 (Jilovec, 2004). As its popularity increased, international bodies started to ratify their own standards. EAN Inter-

Radio Frequency Identification History and Development

Figure 2. Overview of AIDC

Barcode system Optical Character Recognition (OCR)

Fingerprint procedure Biometric MM Voice identification

AutoID Magnetic Smart cards

RFID

Figure adapted from RFID Handbook – Fundamentals and Applications in Contactless Smart Cards and Identification (2nd Ed.), Finkenzeller (2003). Copyright John Wiley & Sons Limited. Reproduced with Permission.

national and Japanese Article Numbering (JAN) are the other widely adopted systems. Barcodes became globally adopted in manufacturing, production, and distribution. There are now advanced barcodes with more data storage capacity such as the two-dimensional (2D) barcodes introduced in 1988 (Anonymous, 2006; Man, 2007). The 2D barcodes use the matrix symbol technology to achieve higher data density than the linear barcode while utilising lesser space. Barcode, as referred to in this chapter, is the one-dimensional, linear barcode widely used in retail, manufacturing, and supply chain. Magnetic stripe is another AIDC widely used in the banking industry. Its standard was established in 1970 (Anonymous, 2007a). It is commonly used on credit and debit cards, and access control cards. The magnetic stripe when run past a reader produces an electromagnetic signal recordable by the reader. Another version of magnetic AIDC is the Magnetic Ink Character

Recognition (MICR). Similarly, MICR is widely used in the banking industry. It is being used for bank cheque authentication. Both technologies were adopted by the American Banking Association (Mullen & Moore, 2005) and banks around the world. Optical Character Recognition (OCR) was introduced in the 1960s, almost twenty years after barcode’s emergence. Like the MICR, special characters that are legible to both humans and machines are used to present a series of unique codes. OCR is also used in the banking industry, production, and service and administrative fields (Finkenzeller, 2003). More recently, biometric and smart cards have attracted interest. There are two main forms of biometric identification, one is voice recognition and the other is fingerprinting. A highly sophisticated system converts voice into digital signals to process the authentication of a subject. Voice identification is now being implemented in sup-

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Radio Frequency Identification History and Development

ply chain management to aid in picking orders (Allen, 1991; Kondratova, 2003). Fingerprinting recognises the unique finger patterns of individuals. As such, its application is commonplace around security and access control. A common application of fingerprinting is the employee time tracking system. Smart cards first gained publicity as a pre-paid telephone card launched in 1984. By 1995, 600 million smart cards were issued (Finkenzeller, 2003). Smart card is a secured data storage device widely used in Global System for Mobile communications (GSM) devices and as cash cards for micro-payments. It has a galvanised input/ output connection with processing capability. An external power source is required to operate the smart card. The card needs to be placed in contact with a reader in order to transfer data. Wear and tear to the smart card processor is inevitable with frequent usage and contact. Another version of the smart card, known as the contactless smart card, uses radio frequency (RF) technology. Data can be transferred without the need to slot the card into a reader, thus no contact with the reader is necessary. The International Organization for Standardisation (ISO) standard for contactless

smart card was developed between 1992 and 1995 (Finkenzeller, 2003). A contactless smart card works in close proximity to a reader. It is thus suitable for applications where masses flow, such as, a high traffic channel. Contactless smart cards are for that reason widely used in public transport ticketing, allowing a quicker, smoother commuter flow through train station barriers or buses doors (Finkenzeller, 2003). The above section shows that AIDC has evolved into a well-received technology for use in electronic payment, access control, production, and distribution. Barcodes and RFID are the two AIDC technologies utilised in supply chains where products are being identified at different stages. The rest of the AIDC technologies are primarily used in security, banking, and public transportation domains. Figure 3 shows the development of AIDC in a time chart.

rfId systeM A RFID system is made up of two main hardware components: tags and readers (Grasso, 2004). The tags or transponders consist of a memory

Figure 3. The development of AIDC

1930s – 1940s Emergence of barcode, magnetic stripes, & RFID.

1949 Barcode patented.

70

1970 Magnetic stripes standard established.

1988 2D Barcodes introduced.

1973 UPC adopted.

1960s Barcode used in railroad system. OCR developed. Magnetic stripes & MICR adopted by the American Banking Association.

1999 2000s EPC developed. RFID for Supply Chain Real time locating 1992 - 1995 systems Contactless card (RTLS). standard developed.

1984 Smart card first used in pre-paid mobile phone.

1995 600 millions of Smart card issued.

2003 Voice Inventory Management System prototype developed.

Radio Frequency Identification History and Development

chip and have a built-in antenna. The memory, depending on its size, can store up to 64K of data. The antenna receives and transmits data using radio waves. There are three basic forms of tag: passive, active, and hybrid or semi-passive. A passive tag does not have an internal power source to process nor transmit signals. An active tag has an integrated battery as the power source. An active tag can broadcast signals and transmit at a longer range than a passive tag. In contrast, a passive tag is only operational when it receives RF signals from an authenticated reader or source. The tag uses the RF as a source of power to transmit data back to the reader, a process called inductive coupling (Weinstein, 2005). A semi-passive tag has an on-board power source and yet behaves like a passive tag. It has a switch that turns on the internal power source when it receives RF signals from a reader. A semi-passive tag overcomes the short range limitation of a passive tag and the complexity of an active tag response method (Jones et al., 2006). Tags can be read only, write once and read many times, or read and write many times. There are six classes of tags: Class 0 to Class 5. A Class 0 tag is a factory programmed read-only passive

tag. Once programmed, the data in the tag cannot be altered. A Class 1 tag is similar to a Class 0 tag except that it can be programmed by the user. It contains minimum features to keep the cost low. A Class 2 tag is a read-write passive tag with a longer communication range than a Class 1 tag. It has extended memory and authenticated access control features not available in Class 1 tags. A Class 3 tag is a semi-passive read-write tag. It has an on-board power source and thus has a longer communication range and higher transmission reliability than Class 2 tags. A Class 4 tag is an active ad-hoc read-write tag with the functionalities of a Class 3 tag. It is capable of communicating with other Class 4 tags within range of its ad-hoc network. A Class 5 tag is an autonomous active read-write reader tag. It has the features of a Class 4 tag and is capable of communicating with all classes within its subsets. As you see, each successive class “is a superset of the functionality contained within, the previous class, resulting in a layered functional classification structure” (Engels & Sarma, 2005, p. 3). Figure 4 shows the layered classification structure of tags. Class 0 is not shown in the figure as it could be classified as Class 1 due to their similar features. Class 1 is

Figure 4. Auto-ID center RFID class structure – layered hierarchy

Reader (Class 5) Active Ad Hoc (Class 4) Semi-Passive (Class 3) Higher Functionality (Class 2) Identity (Class 1) Source: ©2005 Engels & Sarma. Reproduced with Permission.

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Radio Frequency Identification History and Development

Table 1. Frequency Allocation for RFID in the UHF Spectrum Country

Frequency (MHz)

Technique

Regulator Website

Australia

920 to 926

NA

www.acma.govt.au

Brazil

902 to 907.5

FHSS

www.anatel.gov.br

China

840.5 to 844.5 920.5 to 924.5

FHSS

www.mii.gov.cn

Finland

865.6 to 867.6

LBT

www.ficora.fi

France

865.6 to 867.6

LBT

www.arcep.fr

Germany

865.6 to 867.6

LBT

www.bundesnetzagentur.de

Hong Kong

865 to 868 920 to 925

NA

NA

India

865 to 867

NA

www.trai.gov.in

Italy

865.6 to 867.6

LBT

www.agcom.it

Japan

952 to 954

LBT

www.soumu.go.jp

Korea, Rep.

908.5 to 910 910 to 914

LBT FHSS

www.kcc.go.kr

Malaysia

866 to 869

NA

www.cmc.gov.my

New Zealand

864 to 868

NA

www.med.govt.nz

Singapore

866 to 869 920 to 925

NA

www.ida.gov.sg

South Africa

865.5 to 867.6 917 to 921

LBT FHSS

www.icasa.org.za

Spain

865.6 to 867.6

LBT

www.mityc.es

Sweden

865.6 to 867.6

LBT

www.pts.se

Switzerland

865.6 to 867.6

LBT

www.bakom.ch

Taiwan

922 to 928

FHSS

NA

Thailand

920 to 925

FHSS

www.ntc.or.th

Turkey

865.6 to 867.6

LBT

www.tk.gov.tr

United Kingdom

865.6 to 867.6

LBT

www.ofcom.org.uk

United States

902 to 928

FHSS

www.fcc.gov

Vietnam

866 to 869

NA

www.mpt.gov.vn

Source: ©2007 Barthel. (FHSS – Frequency Hopping Spread Spectrum, LBT – Listen Before Talk). Reproduced with Permission.

established as the foundation of the RFID class structure (Engels & Sarma, 2005). Besides the classes of tag, the use of a tag is controlled by the radio frequency spectrum. RFID utilises the Industrial, Scientific, and Medical (ISM) band available worldwide. There are four

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categories of spectra available for commercial use: 125 to 134 KHz in the low frequency category, 13.56 MHz in the high frequency category, 433 MHz and 868 to 928 MHz in the ultra high frequency (UHF) category, and 2.45 GHz in the microwave category (Walker, 2003). There may

Radio Frequency Identification History and Development

be some variation in the classification of spectra due to the different regulatory on the use of ISM band in different parts of the world. In the effort to ensure global interoperability of RFID tags for global roaming applications, EPCglobal has been advocating the use of RFID in the 860 to 960 MHz spectrum. This is the spectrum used in the EPC Class 1 Generation 2 tags that aims at covering a wide group of countries that can use the same tags. As of September 2007, there are a total of 54 countries with regulations in place for the use of RFID within the 860 to 960 MHz spectrum (Barthel, 2007). These countries represent about 92 per cent of the world gross national income. Table 1 shows the allocated frequencies for RFID use in the UHF spectrum by countries. The other component of a RFID system is the reader. A reader sends and receives RF signals. It may be portable or fixed in a position and is linked to a computer. In a proprietary system, readers usually read only proprietary tags. The readers and tags must be programmed within the same range of a spectrum to communicate. Thus, one of the biggest challenges is harmonising the frequency for RFID use in the UHF spectrum, particularly, in Europe where available UHF spectrum is limited (Wasserman, 2007). For example, France, Italy, Spain, and Turkey were using the UHF spectrum for military equipment before the ratification of RFID use in the UHF spectrum (Barthel, 2006). The UHF spectra shown in Table 1 are the approved frequency slots for RFID use in the respective countries. This means that a RFID reader has to be tuned to the approved frequency slots for operation in that country. Therefore, the EPC Class 1 Generation 2 tags can roam internationally among these countries thus allowing a worldwide supply chain visibility in these countries. A reader broadcast its signal within a specific spectrum depending on its power and frequency. The distance a tag and a reader can transmit is relative to the size of the antenna. In a samefrequency band, the larger the antenna, the longer

the transmission range is. The orientation or shape of the antenna is equally important in its role of picking up electromagnetic signals, particularly, when the tag is used on a material that attenuates the electromagnetic signals. Thus the “surface area and the shape of the tag antenna have to be optimised for not only backscattering the modulated electromagnetic wave but also harvesting energy for the microchip to function” (Ukkonen, Schaffrath, Kataja, Sydanheimo, & Kivikoski, 2006, p. 111). There are now many shape and sizes of antennas designed for use on different materials and environments. There are also various transmission methods. The frequency hopping spread spectrum (FHSS) method switches channels at a sequence for a more reliable transmission. The FHSS method allows the efficient use of the bandwidth. The other method used mostly in Europe is the listen before talk (LBT) method. In the LBT, a reader has to listen for other transmitters using the same channel before communicating with the tags through an unused channel (Eeden, 2004). This method is derived due to the restriction on the amount of energy emission in Europe set by the European Telecommunications Standards Institute (ETSI). A LBT reader is allowed to transmit signals for a period of four seconds and then stop the transmission for a least 0.1 second (Anonymous, 2007b; Roberti, 2004). The disadvantage of the LBT method is the slower data transfer rate, which is about thirty percent of the FHSS data rate (Roberti, 2004).

barcodes and rfId RFID is generally thought of as a replacement for barcodes (Atkinson, 2004; Lazar & Moss, 2005; Sheffi, 2004). Barcodes have been around since 1949 when they were first patented. It took almost thirty to forty years for barcodes to gain wide adoption. This is evident in the late 1980s to early 1990s when there were numerous articles on

73

Radio Frequency Identification History and Development

the application and implementation of barcodes; Walter (1988), Carter (1991), Lacharite (1991), Ekman (1992), and Burkett (1993) are examples of barcodes application in the various industries, to name a few. By the 2000s, the barcode is already an established technology. This is also evident in articles claiming barcode is still “alive” amidst the emergence of RFID (Katz, 2006) and proclaiming success stories of barcode implementations (Heinen, Coyle, & Hamilton, 2003; May, 2003). The announcement by the Food and Drug Administration (FDA) in the United States about the use of barcodes for the labeling of medications further strengthen the barcode’s position in the industry (Heinen, Coyle, & Hamilton, 2003). A recent survey by Venture Development Corporation shows that the demand for barcode scanners is strong (Mason, 2005). Therefore the general preconception of RFID replacing barcode needs to be refined. It is important to understand the difference between RFID and barcodes in order to

successfully implement a RFID system especially in a barcode dominant environment. Table adapted from RFID Handbook – Fundamentals and Applications in Contactless Smart Cards and Identification (2nd Ed.), Finkenzeller (2003). Copyright John Wiley & Sons Limited. Reproduced with Permission. Undoubtedly, RFID has far more capability offering more advantages than barcodes. Table 2 shows the differences between the two technologies. Barcode readers use optical technology to capture the patterns of a barcode label. It therefore requires a line of sight within a short distance to read the label. This inevitably calls for the need to locate a barcode label by either pointing a scanner directly at the label or by positioning the label such that it can be read by a fixed scanner. Either way involves labour. By contrast, RFID uses RF or electromagnetic waves as a means of data collection. RF works in omni-direction ally up to a few yards. This attribute enables a

Table 2. RFID and barcode comparison System parameters

Barcode

RFID

Typical data quantity (bytes)

1-100

16-64k

Content

Specific (SKU level)

Dynamic

Machine readability

Good

Good

Readability of people

Limited

Impossible

Line of sight requirement

Yes

No

Influence of dirt

Very high

No influence

Influence of covering

Total failure

No influence

Influence of direction and position

Low

No influence

Influence of metal and liquid

Very low

High

Degradation/wear

Limited

No influence

Reading speed

Low (one label at a time)

Very fast (multiple tag)

Reading distance

0-50cm

0-5m (microwave)

Cost of label/tag

Inexpensive

Expensive

Standards

Defined

Being defined

Stage of maturity

Mature

Evolving

Table adapted from RFID Handbook - Fundamentals and Applications in Contactless Smart Cards and Identification (2nd Ed.), Finkenzeller (2003). Copyright John Wiley & Sons Limited. Reproduced with permission.

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Radio Frequency Identification History and Development

RFID reader to communicate with a tag without the need to be in the line of sight, which has an added advantage of having a reader reading multiple tags simultaneously. This feature of RFID presents the reality of connecting the real world “with its representation in information systems” (Strassner & Schoch, 2002, p. 1). Strassner & Schoch (2002) suggest that the media break, a break between physical and its information, can be avoided with automation, awareness of smart objects, and mobility. Figure 5 shows the progress towards the convergence with the use of RFID (Fleisch, 2001). The capability of reading multiple tags at a given time increases the throughput to a level that barcode cannot achieve. This also eases the bottleneck of scanning each item at a time with a faster reading speed. However, this capability has its downside. The fact that, in a RFID system, tags within range are read almost simultaneously also means that the exact sequence of the cartons is not picked up by the reader (Bednarz, 2004). In a conveyor setup, cartons are often required to be routed to different locations. It is therefore

important to know the order of the cartons in order to direct them to the right locations. Barcode systems have been successful in such scenario. A “bar-code-based system knows more about the order of packages moving along a belt” (Bednarz, 2004, p. 8). An advantage of RF is the ability to communicate in a harsh environment where the barcode label is worn or covered by dust. RF is able to penetrate most types of material. However, the signal is vulnerable to metal, liquid or material with high moisture content, particularly the high frequency range. More energy or power is needed to mitigate the loss of RF propagation through those materials. There are on-going projects to overcome this drawback (Collins, 2004). At a mature stage of development, barcode is relatively inexpensive to implement for a costeffective solution (Anonymous, 1993; Ekman, 1992). A record storage warehouse of 30,000 sq ft uses only two computers and two wand scanners to keep track of thousands of boxes of record files (Anonymous, 1993). Conversely, RFID technology is evolving steadily particularly in the supply

Figure 5. Avoidance of media breaks

Source: ©2001 Fleisch. Reproduced with Permission.

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Radio Frequency Identification History and Development

chain industry. Setting up an RFID infrastructure is expensive and hence requires careful study on systems integration with existing business information systems. The RFID tags make up the main outlay. Each tag costs US$5 in early 2000 down to between US$1 to 50 cents in 2004 as reported by Atkinson (2004). The cost of a tag continues to drop and each tag is expected to cost no more than five cents per tag for mass adoption to take place. In 2006, the five cents per tag benchmark has been achieved at an order of 100 million pieces (Roberti, 2006). The self-regulating market forces necessitate that should prices fall to five cents a tag, the demand for tags will increase. This in turn may create a supply issue with production capacity lacking behind demand (Sarma, 2001). It may push prices back up, thus dwindling the prospect of an earlier mass adoption of RFID technology. Another drawback of RFID is the lack of a harmonised standard across this system. Barcode has clearly defined standards and the different standards are globally accepted. In terms of a unique numbering system for item identification, EPC is one of the standards for RFID. The use of RF is posing a challenge to a globally accepted standard. This is largely due to the different frequency allocation by the local governments. At present, different standards are adopted across different RFID systems complying with the local regulations. Manufacturers, importers and businesses are concerned that their products cannot be tracked across countries’ borders because of different regulations. This would warrant them to use different systems to cater for customers in different parts of the world (Atkinson, 2004). The 13.56 MHz spectrum is commonly used for RFID applications such as proximity access cards to premises, and smart cards. The 433 MHz spectrum is commonly reserved for supply chain use in most countries making it a suitable candidate for global supply chains. It was also considered the industry standard for supply chains (Li, Visich, Khumawala, & Zhang, 2006). The

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China State Radio Regulation Committee on 9th November 2006 approved the use of 433 MHz for RFID devices compatible with the ISO standard. This seems to solidify the 433 MHz spectrum as an international standard (Swedberg, 2006). New Zealand has also assigned the 433 MHz spectrum for RFID and other short range devices. Unfortunately, frequencies in this spectrum do not work reliably under supply chain conditions due to the short wavelength of about one metre (Anonymous, 2004). Thus a passive tag at 433 MHz might not adequately achieve the reading accuracy. The United States Department of Defense (DOD) has tested the interference of 433 MHz active RFID system and maintained there is no interference between the RFID system and radar equipments that they are aware of. However, the DOD is taking precaution not to deploy the RFID systems within forty kilometres of any military radar system (Collins, 2005). EPCglobal on the one hand has ratified various standards for RFID operations. It has ratified the Generation 1 tag in 13.56 MHz, 860 to 930 MHz, and 900 MHz. The latter is factory programmed tag or Class 0 while the others are writeable or Class 1. A notable improved standard of EPCglobal is the Class 1 Generation 2 UHF tags (Wessel, 2007). This standard allows interoperability across the 860 to 960 MHz spectrum making this standard more scalable and raising its tolerance to interference in a dense RF environment. The United States has adopted the 915 MHz frequency as the national standard for passive RFID systems (Porter, Billo, & Mickle, 2006) which is within the EPCglobal defined range for UHF tags. The Australian Communications and Media Authority has issued a license to GS1 for the use of 920 to 926 MHz in Australia. The New Zealand Government has allocated two short range device slots in the 902 to 928 MHz range for RFID experiments. Besides assigning the 864 to 868 MHz spectrum for RFID, the New Zealand Government has plans to freeze any further issuance of licenses in the band of 915 to 921 MHz to cater for future

Radio Frequency Identification History and Development

RFID uses (Anonymous, 2007c). The New Zealand Government is adopting generic frequency standards across the ISM spectrum as a strategy for keeping the use of RFID devices and licensing open. The Government is actively discussing and harmonising the frequency arrangements with key trading partners such as the Australia, Europe, and the United States. Such arrangement will make RF equipments easily available without incurring additional cost for modifying the equipment according to local standards. The European Commission on the other hand has planned to adopt the ultra-wide band frequency range of 3.4 to 4.8 GHz and 6 to 8.5 GHz among the European countries (Swedberg, 2007). Privacy is yet another issue with the use of RFID. While standards and costs are primarily technological, privacy is believed to be an educational one (Twist, 2005). RFID is just another data collection tool for keeping track of products. Sarma (2005) highlights that the electronic toll collection, a form of RFID applications with longer read range than the cheaper RFID/EPC tag, is already in use in many countries. The information in a RFID/EPC tag is encoded and does not contain information about the consumers. It adopts the Internet technology where the information in the tag is used as an address to more information about the content. The access to such further information is secured and authenticated. Another similar application widely used is the credit card.

conclusIon RFID has been in commercial use since the 1970s. As an AIDC technology using wireless communication, RFID enables simultaneous collection of objects data with no or little human intervention. Thus RFID is an important technology from the point of view of ubiquitous computing. RFID is also an emerging technology that performs better than barcodes in most aspects. Of note, RFID’s

unique characteristics offer more utilities than barcodes. An example is the tracking of items without the need for line of sight. Tagging at item level enhances supply chain visibility and security. Manufacturers and retailers can have tighter control over their products from unwanted spoilage to out-of-stock with more accurate and timely data capturing. Although efforts to improve the performance are evident, the impediment to RFID implementation is the lack of standards, the relatively high cost of tag per unit, and privacy (ABIResearch, 2006; C. B. Soon & J. Gutierrez, 2008; Vijayaraman & Osyk, 2006). By far, these are the three main hurdles, among a number of secondary obstacles such as frequency interference, which need to be resolved before the technology can be widely adopted. Unless solutions are found for the three hurdles, barcode is still the cheaper and easier option although the benefits are not as extensive as what RFID can yield. With this stance, it is not to say that RFID will totally replace barcode, at least not in the next twenty to thirty years until a RFID tag is possibly as cheap as a barcode label and when the technology has matured. This projection is in line with what Bhuptani (2005) has noted, namely, that a new technology typically takes twenty to thirty years to become commercialised and forty to fifty years to become fully mature. And so accordingly, RFID has just reached the commercial stage since its inception in the supply chain and thus has another twenty to thirty years before reaching its maturity. Blau (2006) suggests that it will take fifteen years before RFID replaces barcodes and be used to identify products at item level. RFID and barcodes may in fact be complementary to each other having merits in their respective applications. Woolworths has tested out the tracking of dollies and items using both RFID and barcode systems (Alexandra, 2003). It overcame the cost factor of tagging each item with RFID tags by utilising a barcode system and tagging only the dollies that hold the items with RFID tags. Woolworths reported full item-level

77

Radio Frequency Identification History and Development

visibility without the cost of item-level tagging. From a worst case scenario perspective, Jilovec (2004) suggests barcode as a backup for RFID in case of failure. This is sensible since most companies would already have implemented barcode systems. The use of RFID at the UHF 860 to 960 MHz spectrums is now an internationally accepted standard. With the ratification of this standard, there will be more hardware available for the uptake of RFID in supply chains. The remaining challenges would be to enhance the data transfer rate, enable communication in a dense environment, and educate users on privacy concerns. As the technology matures, the investment and operating costs should gradually reduce. RFID is becoming widespread not only in the supply chain, but also in other industries. The advancement of the technology has introduced RFID to many fields as innovators continue to explore the characteristics of RFID. It will continue to find innovation in the field of real time locating system, positioning system, product authentication, and in the sport arena. Like barcodes, RFID is an enabling tool for data capturing and identification. RFID is thus a smart technology that enables the convergence of information with its speedy event’s data capture. It closes up the gap between the physical world and its representation in information systems. The next phase in the field of RFID is to explore the adoption and diffusion of the technology as a business case.

references ABIResearch. (2006). RFID End-User Survey. ABIResearch. Retrieved November 13, 2007, from http://www.abiresearch.com Alexandra, D. (2003). Woolworths counts on RFID for security’s sake. Logistics Management, 42(9), 61.

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Allen, L. G. (1991). Automatic Identification: How Do You Choose It & Where Do You Use It? Automation, 38(7), 30-33. Anonymous. (1993). Bar code technology increases efficiency for off-site records storage firm. Managing Office Technology, 38(11), 65-67. Anonymous. (2004). Active RFID System Frequencies. Retrieved December 21, 2007, from http://www.idtechex.com Anonymous. (2006). How do 2D barcodes work? Who, What, Why? Retrieved April 20, 2008, from http://news.bbc.co.uk/ Anonymous. (2007a). Automatic Identification and Data Capture Technologies - An overview. Retrieved January, 29, 2007, from http://www. aimglobal.org/technologies/aidc_overview.asp Anonymous. (2007b). Electromagnetic compatibility and Radio spectrum Matters (ERM): European Telecommunications Standards Institution. Anonymous. (2007c). An Engineering Discussion Paper on Spectrum Allocations for Short Range Devices: New Zealand Ministry of Economic Development. Atkinson, W. (2004). Web-Based RFID: Hype or Glimpse of the Future? Apparel, 45(6), 24-28. Bahl, P., & Padmanabhan, V. N. (2000). RADAR: An in-building user location and tracking system. Paper presented at the Proceedings of the IEEE Infocom 2000. Barthel, H. (2006). Regulatory Status for Using RFID in the UHF Spectrum. Brussels: GS1. Barthel, H. (2007). Regulatory Status for Using RFID in the UHF Spectrum. Brussels: GS1. Bednarz, A. (2004). RFID joins wireless lineup at UPS. Network World, 21(38), 8.

Radio Frequency Identification History and Development

Bhuptani, M., & Moradpour, S. (2005). RFID Field Guide - Deploying Radio Frequency Identification Systems. NJ: Prentice Hall.

Grasso, J. (2004). The EPCglobal Network. EPCglobal Retrieved December 21, 2007, from http://www.epcglobalus.org

Blau, J. (2006). RFID on all goods is 15 years away, says Metro. Computerworld Retrieved November 16, 2006, from http://www.computerworld.co.nz

Heinen, M. G., Coyle, G. A., & Hamilton, A. V. (2003). Barcoding makes its mark on daily practice. Nursing Management, Oct 2003, 18-20.

Burkett, T. (1993). Bar code implementation. Quality, 32(3), 28. Carter, J. R., & Ragatz, G. L. (1991). Supplier Bar Codes: Closing the EDI Loop. International Journal of Purchasing and Materials Management, 27(3), 19. Collins, J. (2004). New Two-Frequency RFID System. RFIDJournal. Retrieved April 2, 2007, from http://www.rfidjournal.com Collins, J. (2005). Test Detect RFID-Radar Interference. Retrieved December 21, 2007, from http://www.rfidjournal.com Edwards, J. (2008). RFID Is a Winner in the Sports Arena. RFIDJournal. Retrieved April 26, 2008, from http://www.rfidjournal.com Eeden, H. v. (2004). Europe Needs New RFID Regulations. RFIDJournal Retrieved December 21, 2007, from http://www.rfidjournal.com Ekman, S. (1992). Bar Coding Fixed Asset Inventories. Management Accounting, 74(6), 58. Engels, D. W., & Sarma, S. E. (2005). Standardization Requirements within the RFID Class Structure Framework. MA: Auto-ID Labs. Finkenzeller, K. (2003). RFID Handbook - Fundamentals and Applications in Contactless Smart Cards and Identification (2nd ed.). Chichester: Wiley. Fleisch, E. (2001). Business Perspectives on Ubiquitous Computing (M-Lab Working Paper No. 4). St Gallen: University of St Gallen.

Hightower, J., Vakili, C., Borriello, G., & Want, R. (2001). Design and Calibration of the SpotON Ad-Hoc Location Sensing System. University of Washington Retrieved April 26, 2008, from http:// seattle.intel-research.net/people/jhightower// pubs/hightower2001design/hightower2001design.pdf Jilovec, N. (2004). EDI, UCCnet & RFID - Synchronizing the Supply Chain. Colorado: 29th Street Press. Jones, A. K., Dontharaju, S., Tung, S., Hawrylak, P. J., Mats, L., Hoare, R., et al. (2006). Passive active radio frequency identification tags. International journal of Radio Frequency Technology and Applications, 1(1), 52-73. Katz, J. (2006). Bar Codes: Alive and Well. Industry Week, 255(7), 14. Kondratova, I. (2003). Voice and multimodal access to AEC project information. Paper presented at the The 10th ISPE International Conference on Concurrent Engineering: The Vision for Future Generations in Research and Applications, Portugal. Lacharite, R. (1991). Rethinking Bar Coding: Turning Preconceptions into System Tools. ARMA Records Management Quarterly, 25(2), 3. Landt, J. (2001). Shrouds of Time. The history of RFID Retrieved 19 January, 2006, from http:// www.aimglobal.org/technologies/rfid/resources/ shrouds_of_time.pdf

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Lazar, L. D., & Moss, H. K. (2005). Radio Frequency Identification Technology: An Introduction. Paper presented at the Proceedings of the 2005 Southern Association for Information Systems Conference, Savannah. Li, S., Visich, J. K., Khumawala, B. M., & Zhang, C. (2006). Radio frequency identification technology: applications, technical challenges and strategies. Sensor Review, 26(3). Man, M. (2007). All About 2D Bar Codes. Socket Communications Technology Brief. Retrieved April 20, 2008, from http://www.socketmobile. com Mason, B. (2005). Bar Code Scanner Demand Remains Strong (Press Release). Massachusetts: Venture Development Corporation. May, E. L. (2003). The case for bar coding: Better information, better care and better business. Healthcare Executive, 18(5), 8-13.

Sarma, S. (2001). Towards the 5-cent Tag. MA: Auto-ID Labs. Sarma, S. (2005). A History of the EPC. In S. Garfinkel & B. Rosenberg (Eds.), RFID Applications, Security, and Privacy (pp. 37-55). NJ: Addison-Wesley. Sheffi, Y. (2004). RFID and the Innovation Cycle. The International Journal of Logistics Management, 15(1). Shepard, S. (2005). Radio Frequency Identification. NY: McGraw-Hill. Smucker, T. (2006). Making the GS1 Vision a Reality (Annual Report). Brussels: GS1. Soon, C. B., & Gutierrez, J. (2008, May 18-20). Where is New Zealand at with Radio Frequency Identification in the Supply Chain? - A Survey Result. Paper presented at the Proceedings of 2008 International Conference on Information Resources Management, Niagara Falls, Canada.

Mullen, D., & Moore, B. (2005). Automatic Identification and Data Collection: What the future holds. In S. Garfinkel & B. Rosenberg (Eds.), RFID Applications, Security, and Privacy (pp. 3-13). NJ: Addison-Wesley.

Soon, C. B., & Gutierrez, J. A. (2008). Effects of the RFID Mandate on Supply Chain Management. Journal of Theoretical and Applied Electronic Commerce Research, 3(1), 81-91.

Ni, L. M., Liu, Y. H., Lau, Y. C., & Patil, A. P. (2004). LANDMARC: Indoor Location Sensing Using Active RFID. Wireless Networks, 10, 701-710.

Strassner, M., & Schoch, T. (2002). Today’s Impact of Ubiquitous Computing on Business Processes. Paper presented at the First International Conference on Pervasive Computing, Zurich, Switzerland.

Porter, J. D., Billo, R. E., & Mickle, M. H. (2006). Effect of active interference on the performance of radio frequency identification systems. International journal of Radio Frequency Technology and Applications, 1(1). Roberti, M. (2004). New ETSI RFID Rules Move Forward. RFIDJournal. Retrieved December 21, 2007, from http://www.rfidjournal.com Roberti, M. (2006). SmartCode Offers 5-Cent EPC Tags. RFIDJournal. Retrieved April 26, 2008, from http://www.rfidjournal.com

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Swedberg, C. (2006). China Endorses ISO 18000-7 433 MHz Standard. RFIDJournal Retrieved July 29, 2007, from http://www.rfidjournal.com/ Swedberg, C. (2007). EC Spectrum Decision Expected to Boost UWB RFID Adoption. RFIDJournal. Retrieved December 29, 2007, from http://www.rfidjournal.com Swedberg, C. (2008a). RFID Fuels Gas Tank Sercurity. RFIDJournal. Retrieved April 26, 2008, from http://www.rfidjournal.com

Radio Frequency Identification History and Development

Swedberg, C. (2008b). U.S. FDA Seeks Research for Medical Device Tracking System. RFIDJournal. Retrieved April 26, 2008, from http://www. rfidjournal.com Twist, D. C. (2005). The impact of radio frequency identification on supply chain facilities. Journal of Facilities Management, 3(3), 226-239. Ukkonen, L., Schaffrath, M., Kataja, J., Sydanheimo, L., & Kivikoski, M. (2006). Evolutionary RFID tag antenna design for paper industry applications. International journal of Radio Frequency Technology and Applications, 1(1), 107-122. Vijayaraman, B. S., & Osyk, B. A. (2006). An empirical study of RFID implementation in the warehousing industry. The International Journal of Logistics Management, 17(1), 6-20. Violino, B. (2006). APL Reaps Double Benefits From Real-Time Visibility [Electronic Version]. RFIDJournal. Retrieved December 28, 2006 from http://www.rfidjournal.com. Walker, J. (2003). What You Need To Know About RFID in 2004. Forrester Research. Retrieved December 20, 2003, from http://www. forrester.com

key terMs AIDC: Automatic Identification and Data Capture. EPC: Electronic Product Code. EPCglobal: An international subscriberdriven organization aimed at enhancing RFID standards. GS1: Former Uniform Code Council (UCC) and European Article Numbering (EAN) International. ISM: Radio bands available worldwide reserved for use in the Industrial, Scientific, and Medical fields. ISM bands range from 6.765 MHz to 246 GHz. RF: Radio Frequency. RFID: Radio Frequency Identification. Supply Chain Management: The managing of all movements of products and materials from source to point of consumption including storage.

Walter, E. J. (1988). Bar Code Boom Extending thru Industry. Purchasing World, 32(2), 39.

Tag: A transponder with built-in memory chip and antenna encoded with an identifier. It can be passive (without battery) or active (with battery).

Wasserman, E. (2007). Europe Embraces EPC Slowly. RFIDJournal. Retrieved December 21, 2007, from http://www.rfidjournal.com

endnote

Weinstein, R. (2005). RFID: A Technical Overview and Its Application to the Enterprise. IT Professional Magazine, 7(3), 27-33.

1

Uniform Code Council and EAN International merged to form GS1.

Wessel, R. (2007). European EPC Competence Center Releases UHF Tag Study. RFIDJournal. Retrieved July 16, 2007, from http://www.rfidjournal.com This work was previously published in Auto-Identification and Ubiquitous Computing Applications: RFID and Smart Technologies for Information Convergence, edited by J. Symonds, J. Ayoade & D. Parry, pp. 1-17, copyright 2009 by Information Science Reference (an imprint of IGI Global).

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Chapter 1.8

Automated Data Capture Technologies: RFID

Vidyasagar Potdar Curtin University of Technology, Australia Chen Wu Curtin University of Technology, Australia Elizabeth Chang Curtin University of Technology, Australia

abstract In this chapter we provide an introduction to RFID technology. We discuss the main components of the RFID technology, which includes RFID transponders, RFID readers, RFID middleware, and RFID labels. A detailed classification and explanation for each of these components is provided, followed by the benefits and applications that can be achieved by adopting this technology. After discussing all possible applications, we describe

the business benefits and how stakeholders can benefit. This is followed by a detailed outline of the adoption challenges, where we discuss issues like the security, privacy, cost, scalability, resilience, and deployment and some existing solutions. Once the issues are discussed, we divert our attention to some successful RFID deployment case studies to describe the adoption of RFID technology that has already begun and how many big organizations across the world are showing interest in this technology. Since this chapter takes into consideration

Copyright © 2010, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Automated Data Capture Technologies

a variety of audiences like researchers, business executives, business consultants, hobbyists, and general readers, we tried to cover material relevant to each target audience. For business executives and consultants interested in knowing who can offer complete RFID solutions, we allocated a dedicated section for RFID vendors where we provide a comprehensive list of RFID vendors across the globe. For researchers, we listed some open issues in the section of adoption challenges. For advanced users, in-depth technical details are provided in the section where we discuss security and privacy enhancing protocols.

IntroductIon Automated data capture is an important aspect in supply chain management and logistics. In the last decade, automated identification and data capture (AIDC) has revolutionized the overall supply chain management process. AIDC includes technology to identify objects, and automatically collects data about them and updates the data into software systems without human intervention. Some examples of AIDC technologies include bar codes, RFID, smart cards, voice and facial recognition, and so forth. An automated inventory control systems (AICS), which forms the backbone of the modern supply chain, is a software application used in a warehouse to monitor the quantity, location, and status of inventory. Modern AICS heavily relies upon barcodes, for automated data capture. A barcode basically is a machine-readable visual representation of information printed on the surface of objects. There are several different kinds of barcodes, for example, barcodes which store data in the widths and spacing of printed parallel lines, and those that store data within the patterns of dots, or concentric circles, or even hidden within images. This encoded data on the barcodes is read by barcode readers, which up-

date the backend ERP, SCM, or WMS systems. However there are some inherent issues with using a barcode, for instance, barcodes become ineffective in rain, fog, snow, dirt and grime, and so forth (Tecstra, n.d.). Since barcodes rely on optical sensors, any minor change on the barcode print can make it difficult to read. This can be commonly seen at point of sale (POS) in the supermarkets, where the POS operator scans the barcode several times because it is either wet or not aligned properly. To overcome these issues the industry is now looking at the possibility of using new generation AIDC technology like the RFID. A radio frequency identifier (RFID) system is basically composed of an RFID transponder (tag) and an RFID interrogator (reader). The RFID transponder or the RFID tag (which is how it is often called) is a microchip connected to an antenna. This tag can be attached to an object, which needs to be uniquely identified, for example, it can be used in a warehouse to track the entry and exit of goods. This tag contains information similar to the barcode, which stores the unique properties of the object to which it is attached. An RFID reader can access this information. The RFID reader communicates with the RFID tag using radio waves. The radio waves activate the RFID tag to broadcast the information it contains. Depending on the type of tag used, the information transmitted could be merely a number or detailed profile of the object. The data fetched from the reader can then be integrated with the backend ERP or SCM or WMS systems (Tecstra, n.d.). There are two fundamental differences between the conventional barcodes and the contemporary RFIDs. First, RFIDs do not require line of sightthat is, objects tagged with RFID can be sensed in a wide area, and there is no need to individually scan all the objects in front of an optical scanner. Second, RFIDs offer item-level taggingthat is, each item within a product range can be uniquely identified (e.g., “109839 is a bottle

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of orange juice manufactured by ABC Company”). However barcodes do not identify individual items; they can only identify that “this is a bottle of orange juice manufactured by ABC Company.” Some other points could also be considered. RFID has a longer read range compared to barcodes. The amount of data stored on barcodes is limited and often cannot be updated once it is printed. In comparison, RFID tags offer a considerably large amount of data storage capacity as well as reprogramming capabilities, which means the data on the tag can be updated effortlessly. These changes can be done without physically identifying the tag because the RFID reader can uniquely query the desired RFID tag and make the changes. From the security perspective RFID tags can be placed inside the objects, however barcodes have to be printed outside. Another issue with barcodes is the printing quality; substandard printing can result in reading errors (Gloeckler, n.d.; Tecstra, n.d.). There are several inherent advantages with RFID technology; however to achieve widespread adoption of RFID, issues like security, privacy, and cost should be addressed first. In this chapter we provide a detailed insight into RFID. The rest of the chapter is organized in the following manner. The next section introduces the RFID technology. We discuss RFID tags, RFID readers, and RFID middleware. We then discuss the benefits that stakeholders can achieve by adopting RFID technology and provide an RFID Deployment Roadmap. In this section we also describe the steps that an organization should consider prior to adopting RFID to streamline its business process. The fifth section discusses the RFID adoption challenges where we outline the existing issues, which are the major obstacles in widespread adoption. These issues are security, privacy, and cost. Finally, before concluding the chapter, we discuss three case studies in the supply chain domain that have adopted RFID to enhance their business process and gain a competitive advantage.

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The main objectives of this chapter are: 1.

To provide RFID novices with an introductory illustration of the contemporary data capture technologyRFID. This is covered in the next section of this chapter. 2. To offer RFID advanced users a comprehensive survey of RFID technology from both technical and business perspectives. This is covered in detail in the following sub-sections where we give an in-depth explanation of the different types of RFID tags, RFID readers, and RFID middleware. 3 . To illustrate the well-identified RFID adoption challenges and their corresponding deployment strategies for business consultants. This is covered later in the chapter, where we begin by highlighting the main challenges for RFID adoption which include cost, security, and privacy. We then provide a road map for RFID adoption where we provide a detailed deployment strategy for RFID adoption in a business environment. This can facilitate consultants, CEOs, and CIOs to make informed decisions. 4. To explain benefits of adopting RFID solutions to business executives using real-world proven case studies. We do this by highlighting the benefits that RFID offers to different stakeholders, and later in the chapter relating that to five successful RFID deployment case studies from supply chain domains. All these case studies provide an insight into how RFIDs can facilitate businesses across multiple domains.

technology overvIeW An RFID system is composed of three main elements: an RFID tag (inlay), which contains data that uniquely identifies an object; an RFID reader, which writes this unique data on the tags and,

Automated Data Capture Technologies

Figure 1. RFID architecture (Source: Potdar, Wu, & Chang, 2005)

when requested, can read this unique identifier; and an RFID middleware, which processes the data acquired from the reader and then updates it to the backend database or ERP systems (Weis, Sarma, Rivest, & Engels, 2004). A typical RFID system is shown in Figure 1. When the RFID tag comes in the range of the RFID reader, the reader activates the tag to transmit its unique information. This unique information is propagated to the RFID middleware, which appropriately processes the gathered information and then updates the backend database.

once, and read-many. Finally, the tags can also be classified based on the frequency in which they operateLF, HF or UHF.

Active vs. Semi-Active (or Semi-Passive) vs. Passive RFID Tags •

rfId tags An RFID tag is a microchip attached with an antenna to a product that needs to be tracked. The tag picks up signals from the reader and reflects back the information to the reader. The tag usually contains a unique serial number, which may represent information, such as a customer’s name, address, and so forth (RFID Journal, 2006a). A detailed classification is discussed next.

Classification RFID tags can be classified using three schemes. First, the tags can be classified based on their ability to perform radio communicationactive, semi-active (semi-passive), and passive tags. Second, the tags can be classified based upon their memoryread-only, read-write or write-

•

Active tags have a battery that provides necessary energy to the microchip for transmitting a radio signal to the reader. These tags generate the RF energy and apply it to the antennae and transmit to the reader instead of reflecting back a signal from the reader (Lyngsoe, n.d.). These batteries need to be recharged or replaced once they are discharged. Some tags have to be disposed off when the batteries run out of power (Gloeckler, n.d.; Tecstra, n.d.). These tags have a read range of several 100 meters and are very expensive (more than US$20), and hence are used for tracking expensive items; for example, the U.S. military uses these tags to track supplies at ports (Lyngsoe, n.d.; RFID Journal, 2006a). Semi-active tags (or semi-passive or batteryassisted) also contain a battery, which is used to run the circuitry on the microchip, however it still relies on the reader’s magnetic field to transmit the radio signal (i.e., information). These tags have a larger range because all the energy supplied by the reader

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Figure 2. Radio frequency spectrum (Adapted from http://en.wikipedia.org/wiki/Super_high_frequency)

Radio spectrum ELF

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can be reflected back to the reader (RFID Journal, 2006a), which means it can work at low-power signal levels as well. These tags have a read range up to 100 meters and may cost a dollar or more (Lyngsoe, n.d.; RFID Journal, 2006a). Some of these tags often are dormantthat is, they are activated by the presence of a reader’s magnetic field. Once activated, the battery runs the circuitry and responds back to the reader. This is a mechanism to save the battery power (RFID Journal, 2006a). Passive tags completely rely on the energy provided by the reader’s magnetic field to transmit the radio signal to and from the reader. It does not have a battery. As a result, the read range varies depending upon the reader used (Lyngsoe, n.d.). A maximum distance of 15 meters (or 50 feet) can be achieved with a strong reader antennae and RF-friendly environment (Sweeney, 2005).

Read-Write vs. Read-Only RFID Tags •

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Read-only tags: The reader can only read data stored on such tags. The data cannot be modified in any manner. The tag manufacturer programs the data on the tag. Such tags are comparatively very cheap (Tecstra, n.d.). Write-once read-many (WORM): The owner of the tag can program the data by

•

writing the content on the tag. Data stored on this tag can be written only once, however it can be read many times (Sweeney, 2005; Tecstra, n.d.). Read-write tags: Data stored on such tags can be easily edited when the tag is within the range of the reader. Such tags are more expensive and are not often used for commodity tracking. These tags are reusable; hence they can be reused within an organization (Tecstra, n.d.).

LF vs. HF vs. UHF vs. Microwave Frequency RFID Tags RFID systems are classified as radio systems because they generate and radiate electromagnetic waves. Hence the RFID systems should operate within certain frequency limits like the LF, HF, or UHF. Since some of the frequencies are already in use by police, security services, industry, medical, or scientific operations, there is a limited number of frequencies available for RFID systems to operate. Figure 2 shows the radio frequency spectrum (Beherrschen, n.d.). RFID systems operate in four frequency bands: LF, HF, UHF, and Microwave. The RFID tags designed to operate in this frequency have special characteristics. We now discuss each of these kinds of RFID tags in detail.

Automated Data Capture Technologies

Low Frequency (LF) In LF range, RFID tags operate at 125 kHz or 134.2 kHz frequency (Lyngsoe, n.d.; RFID Journal, 2006a; RMOROZ, 2004). Some important characteristics of these tags are as follows:

tags are as follows:

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•

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•

•

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•

•

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Tags in this range are not affected by metallic surroundings and hence are ideal for identifying metal objects like vehicles, tools, containers, and metallic equipments. The reading range varies from a few centimeters to a meter depending upon the size of the antennae and the reader used (RFID Journal, 2006a; RMOROZ, 2004). These tags can also penetrate through water and body tissues, and hence often used for animal identification (RMOROZ, 2004). These are often used at places where tagged objects are moving at a lower speed and very few objects are scanned per second (Lyngsoe, n.d.). Most car immobilizers rely on LF tags. The tag is embedded in the key while the reader is mounted in the ignition area (RMOROZ, 2004). Data transfer rate is low, for example, 70ms for read operation. This is because at low frequency the communication is slower. In an industrial setting, electric motors can interfere with LF RFID operation (RMOROZ, 2004). Most LF-based systems can only read one tag at a time—that is, they do not support reading multiple tags simultaneously (RMOROZ, 2004). These tags are more expensive ($2 or more) to manufacture than the HF tags because of the size of the antennae (RMOROZ, 2004). This frequency is used worldwide without any restrictions.

High Frequency (HF) In the HF range, RFID tags operate at 13.56 MHz (Lyngsoe, n.d.; RFID Journal, 2006a; RMOROZ, 2004). Some important characteristics of these

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• • •

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HF tags can penetrate through most materials including water and body tissues, however they are affected by metal surroundings (Gloeckler, n.d.; RMOROZ, 2004). The thickness of the tag is typically less than 0.1mm and comes with variable antennae sizes. Bigger antennae offer more communication distance. The reading range is normally less than a meter (100cm). HF tags are comparatively cheaper (less than $1) than the LF tags. The data transfer rate is higher compared to LF tags, for example, 20ms for read operation. This is because at high frequency the communication is faster. In an industrial setting, electric motors do not interfere with HF RFID operation (RMOROZ, 2004). The reader can read multiple tags simultaneously. This is termed as anti-collision. There are many anti-collision protocols to prevent the reader from reading the same tag more than once. Depending upon the reader used, at least 50 tags can be read simultaneously (RMOROZ, 2004). HF tags normally work best when they are in close range with the reader (around 90cm). Secondly the orientation of the tags with respect to the reader plays a major role. For optimum communication range, the tag and the reader should be parallel. If however they are perpendicular, the communication range may reduce dramatically (RMOROZ, 2004). In Canada, Shell uses HF RFID for its Easy Pay customer convenience program. In Hong Kong Octopus card is used in public transit service. In the Netherlands, the Trans Link System uses contact-less smart cards to offer contact-less ticket solutions. The World Cup in Germany used tickets embedded with HF

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•

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tags (RMOROZ, 2004). This frequency is used globally without any restrictions. However in certain countries the power of the reader is restricted. Global standard: ISO 15693, 14442, 18000-3.

Ultra High Frequency (UHF) In the UHF range, RFID tags operate at 433 MHz, 860-956 MHz, and 2.45 GHz (Lyngsoe, n.d.; RFID Journal, 2006a; RMOROZ, 2004). Most research work is dedicated to RFID in the frequency range of 860-956 MHz. Some important characteristics of these tags are as follows: •

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• •

•

• •

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Multiple tags can be read simultaneously, for example, at least 200 tags (theoretically 800 possible) (RMOROZ, 2004). UHF tags operating at 860-956 MHz frequencies offer better read range by using short antennas. The reading range is normally 3-6 meters (RMOROZ, 2004). UHF tags are normally less expensive than HF tags because of low memory capacity and simple manufacturing process (RMOROZ, 2004). Such tags are commonly used on objects that are moving at a very high speed, and a large number of tags are scanned per second in the business contexts such as supply chain, warehouse, and logistics. These devices may have a range of 7.5metres (or 25 feet) or more (Lyngsoe, n.d.; Tecstra, n.d.). UHF tags do not work well in liquid and in metal surroundings. Larger read range limits their use to banking and access control applications, because the access card may be scanned from a longer distance and some unauthorized person might gain entry in restricted premises on your behalf. One major hindrance for widespread adoption of UHF RFID is lack of globally accepted regulations. For example, in Australia UHF operates in the 918-926 MHz range, in North

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America UHF operates at 902-928 MHz, in Europe it operates at 860-868 MHz, while in Japan it operates at 950-956 MHz. Secondly, it operates in a highly crowded frequency range because most of the ISM (industrial, scientific, and medical) applications operate in the same range.

Components There are four main components of a RFID tag: microchip, antennae, substrate, and in some cases an additional battery.

Microchip An RFID tag contains a small microchip, which has some computing capabilities limited to simple logical operations and is also used for storage. The storage can be read-only, read-write, write-once read-many (WORM), or any other combination. The storage memory is used to hold a unique identification number that can identify each tag uniquely. Current generation passive tags have a memory capacity of 96 bits (characters). Passive tags have enough space to hold the identification number, however the active tags can have some additional information like the content of the container, its destination or origin, and so forth (Sweeney, 2005; Tecstra, n.d.).

Antennae The tag antenna is the conductive element that enables the transmission of data between the tag and the reader (RFidGazzete, n.d.). Antennae play a major role in deciding the communication distance; normally a larger antenna offers more area to capture electromagnetic energy from the reader and hence provides a greater communication distance. There are several kinds of antennae, like the rectangular planar spiral antenna, fractal antennas,1 and microstrip patch antenna (monopole, dipole). Different types of tags have different

Automated Data Capture Technologies

kinds of antennas, for example, low-frequency and high-frequency tags usually have a coiled antenna that couples with the coiled antenna of the reader to form a magnetic field (RFidGazzete, n.d.). UHF tag antennas look more like old radio or television antennas because UHF frequency is more electric in nature (Sweeney, 2005). Recent advances in technology have even facilitated the deployment of printed antennas to achieve similar functionality like the traditional antennas. One possible way of printing antennas is to use silver conductive inks on plastic substrates or papers (Tecstra, n.d.). The main advantage of printed antennas is that they are cheap.

Substrate

Data Retention Time This attribute describes the time for which the data can be retained on the tag, for example, RII16-114A-01 from Texas Instruments has a data retention time of more than 10 years.

Memory This attribute describes the available memory on the tag. It can be classified as factory-programmed read-only memory and user-programmable memory.

Programming Cycles

This is a chemical (or material) that holds the antennae and the microchip together. It is something like a plastic film (Sweeney, 2005).

This attribute defines the number of times the tag can be reprogrammed. This programming cycle is normally measured at a standard temperature (25 degrees).

Battery

Antennae Size

Unlike passive tags, active RFID tags contain a battery to power the circuitry, and generate and transmit radio signals to the reader. Onboard power supply can enable long-distance communication, as long as 1 kilometer (Sweeney, 2005).

This attributes defines the size of the tag antennae, for example, RI-I16-114A-01 has an antennae of the following dimensions: 24.2 mm +0.1mm/-0.2mm.

attributes

This is the material used to join the antennae with the microchip. Normally Polyethylenetherephtalate is used as a substrate.

RFID tags can be differentiated based on several attributes. In this section we discuss seven main attributes, which should be considered when selecting RIFD tags.

Operating Frequency This describes at what frequency the tag is designed to operate. As discussed earlier RFID tags can either operate in LF, HF, or UHF range of the radio spectrum.

Base Material

Operating Temperature This attribute describes the range in which the tag can operate, for example, RI-I16-114A-01 operates within -25°C to +70°C.

rfId readers RFID readers send radio waves to the RFID tags to enquire about their data contents. The tags then

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respond by sending back the requested data. The readers may have some processing and storage capabilities. The reader is linked via the RFID middleware with the backend database to do any other computationally intensive data processing. There are two different types of RFID readers (Gloeckler, n.d.).

Classification RFID readers can be classified using two different schemes. First, the readers can be classified based on their location as handheld readers and fixed readers. Second, the tags can be classified based upon the frequency in which they operatesingle frequency and multi-frequency.

Fixed Readers vs. Handheld Readers •

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Fixed RFID Readers are fixed at one location (e.g., choke point). In a supply chain and warehouse scenario, the preferred location of a reader can be along the conveyor belt, dock door antennae or portals, depalletization stations, or any other mobile location. Portable or Handheld RFID Readers are designed for Mobile Mount Applications, for example, vehicles in a warehouse or to be carried by inventory personnel, and so forth.

Single Frequency vs. Multi-Frequency •

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Single-frequency operation readers operate in one frequency zone, either in LF, HF, or UHF. Such readers become inconvenient if tags in a warehouse are operating in different frequencies. Multi-frequency operation readers can operate in multiple frequencies. Such readers can conveniently read tags, which operate in different frequencies (i.e., LF, HF, or UHF). Hence these are more useful from a practical perspective, however such readers come at a premium price.

Components There are two main components in a RFID reader: antennae and the input/output (I/O) controller.

Antennae Every RFID reader is equipped with one or more antennas. These antennas generate the required electromagnetic field to sense the RFID tags. There are many different kinds of antennas like linearly polarized, circularly polarized, or ferrite stick antennas.

I/O Controller The data that the reader collects needs to be sent to the organization’s information system like ERP or WMS. Such a communication can be achieved by using RS-232,2 RS-485, or Ethernet. Some new generation readers also provide the Power over Ethernet (PoE) and 802.11 wireless connectivity protocol. Mostly all the readers possess a serial port for programming and data transfer. The manufacturer of RFID readers normally supplies the controllers. These controllers typically operate on 120V AC or 24V DC current.

attributes RFID readers can be differentiated based on several attributes. In this section we discuss 12 main attributes that should be considered when selecting RIFD readers.

Weight Weight of the reader is an important factor if the reader is mobile or handheld because it should be handy and should not cause inconvenience for its user.

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Communication Interface

Time for Identifying Tags

Every reader has a communication interface (e.g., RS232 or Ethernet 10/100BaseT or Wireless 802.11g or infrared data connection) to transfer the data gathered from the RFID tags.

This refers to the time that is necessary to identify tags. The number of tags identified per second varies with the type of readers, for example, IP3 Intellitag Portable Reader (UHF) (Intermec, 2006b) can identity six tags per second.

Integrated Filtering Component

Read Rate & Write Rate The need to filter RFID tag information is vital and usually can be done using a separate server in the RFID middleware or at the place where the reader is mounted. However in order to increase efficiency, reduce cost, and decrease potential points of failure in the network, it would be desirable if the reader itself is equipped with some computing power to facilitate information filtering before propagating an excessive large amount of data to RFID middleware or backend systems (e.g., ERP). New generation readers do offer such a facility like the IF5 Intellitag Fixed Reader, which is built on Linux platform, which runs IBM’s WebSphere® Everyplace® Micro Environment (WEME) (Intermec, 2006a). Some handheld readers are equipped with 700 Series Color mobile computers to do a similar job (Intermec, 2006b).

Antennae (Type and Number) Several antennas can connect a single reader at the same time. There are different kinds of antennas that are equipped with standard readers, for example, the IP3 Intellitag Portable Reader (UHF) (Intermec, 2006b) comes with integrated circular polarized antennas. The advantage of such antennas is that it can read tags in any orientation.

Software Most of the industry standard-compliant RFID readers are equipped with software to setup and re-configure the reader to enhance the resilience of the RFID systems.

This term usually describes the number of tags that can be read within a given period of time. It can also represent the maximum rate at which data can be read from a tag. The unit of measurement is in bits or bytes per second (RFID Journal, 2006b). Write rate usually describes the rate at which information is transferred to a tag, written into the tag’s memory and verified as being correct (RFID Journal, 2006b). The unit of measurement is in number of bits or bytes written per second per tag.

Volatile Memory Some readers have inbuilt volatile memory to retain a certain number of tag IDs.

Frequency Range This term is used to describe the reader’s capability to read tags in different frequencies. Some readers only operate in the UHF frequency (Intermec, 2006b), while others operate in the LF or HF range.

Operating Temperature Depending upon the application, the operating temperature of the reader should be considered. For example, if you are going to deploy an RFID reader in the desert, it should function properly in the extreme temperature. On the other hand, if it is to be deployed in extreme freezing condi-

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tions, the same should also be considered. Many industry standard readers operate within the range of -40°C to 50°C. Apart from the operating condition the storage conditions should also be considered. Normally the storage temperate has a bit higher range.

Miscellaneous Factors Similar to temperature, humidity is also a factor that should be considered when selecting a proper reader. Many readers can operate in 10% to 90% humidity levels (Intermec, 2006c).

Shock Resistance In an industrial setting, shocks are almost inevitable. Hence the reader should be resistant against these conditions as well. Likewise, frequent vibrations in the industry setting give rise to vibration-resistant readers.

Legal Restrictions Some countries have restrictions on using some frequencies because they may be allocated to ISM applications, hence before buying a reader, the country’s legal restrictions should be checked.

rfId Middleware In a general, the RFID middleware manages the readers and extracts electronic product code (EPC) data from the readers; performs tag data filtering, aggregating, and counting; and sends the data to the enterprise warehouse management systems (WMSs), backend database, and information exchange broker. Figure 1 shows the relationship between tag, reader, RFID middleware, and backend database. An RFID middleware works within the organization, moving information (i.e., EPC data) from the RFID tag to the integration point of high-level supply-chain management systems through a series of data-related services. From

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the architectural perspective, RFID middleware has four layers of functionality: reader API, data management, security, and integration management. The reader API provides the upper layer of the interface interacting with the reader. Meanwhile, it supports flexible interaction patterns (e.g., asynchronous subscription) and an active “context-ware” strategy to sense the reader. The data management layer mainly deals with filtering redundant data, aggregating duplicate data, and routing data to appropriate destination based on the content. The integration layer provides data connectivity to legacy data source and supporting systems at different integration levels and thus can be further divided into three sub-layers as specified in Leaver (2005): application integration, partner integration, and process integration. The application integration provides varieties of reliable connection mechanisms (e.g., messaging, adaptor, or the driver) that connect the RFID data with existing enterprise systems such as ERP or WMS. The partner integration enables the RFID middleware to share the RFID data with other RFID systems via other system communication components (e.g., the Data Exchange Broker in Figure 3). The process integration provides capability to orchestrate the RFID-enabled business process. The security layer obtains input data from the data management layer, and detects data tampering which might occur either in the tag by a wicked RFID reader during the transportation or in the backend internal database by malicious attacks. The overall architecture of RFID middleware and its related information systems in an organization are depicted in Figure 3. The backend DB component stores the complete record of RFID items. It maintains the detailed item information as well as tag data, which has to be coherent with those read from the RFID. It is worth noting that the backend database is one of the data-tampering sources where malicious attacks might occur to change the nature of RFID item data by circumventing the protection of an organization’s firewall. The

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Figure 3. RFID middleware architecture

WMS integrates mechanical and human activities with an information system to effectively manage warehouse business processes and direct warehouse activities. The WMS automates receiving, put-away, picking, and shipping in warehouses, and prompts workers to do inventory cycle counts. The RFID middleware employs the integration layer to allow real-time data transfer towards the WMS. The data exchange broker is employed in this architecture to share, query, and update the public data structure and schema of RFID tag data by exchanging XML documents. Any update of the data structure will be reflected and propagate to all involved RFID data items stored in the backend database. From the standardization view, it enables users to exchange RFID-related data with trading partners through the Internet. From the implementation angle, it might be a virtual Web services consumer and provider running as peers in the distributed logistics network.

benefIts to supply chaIn stakeholders The main benefits for stakeholders of adopting RFID in their business processes are manifold. In this section, we summarize these benefits and categorize them based on different potential supply chain stakeholders (as shown in Figure 4) who would benefit from deploying the RFID technology. After reading this section, readers are able to foresee several major advantages from their own perspectives.

Benefits to Manufacturers For manufacturers, RFID is able to support quality control by querying components and subassemblies as they enter the facility. For example, it can ensure that the correct components are included in an assembled item by automatically checking

Figure 4. The stakeholders in the supply chain

Manufacturer

Distribution Center

Warehouse

Logistics Company

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that all items from the Bill of Material are in place. Moreover, if used with appropriate modeling tools, it can help to predict the demand and supply for the products, which in turn determines the manufacturing plan, which is an essential input for the modern ERP and MRP systems.

Benefits to Distribution Centers For distribution centers (DCs), RFID can improve its reception processthat is, a guard confirms the truck’s appointment time, barcodes the trailer, and assigns a parking spot or dock. In particular, such an improvement is achieved by: (a) the RFID reader, which confirms the arrival of the truck, trailer, and all the items, eliminating the need to check the driver’s Bill of Loading; (b) the RFID reader can ‘query’ (scan) the contents much quicker than barcoding the trailer manually; (c) the RFID system can enable the DC gate to communicate with the warehouse management system in a timely manner, thus attaining the steady ‘information synchrony’. In doing so, the productivity of DC is undoubtedly enhanced. The RFID solution is also seen to be beneficial when managing claims and deductions occurring at the DCs (Symbol Technologies, 2004).

Benefits to Warehouses For warehouses, RFID can first improve the product flow by: (a) increasing the Putaway Accuracythe measurement of the accuracy of the process that physically places inventory products into storage; and (b) removing the need for additional barcodes on the pallet. Furthermore, the RFID system can improve the temporary storage. For example, with the support of RFID, inventory items can be ‘scanned’ wherever they are placed, which enables a more flexible storage environment. The RFID reader can help to identify any potential inventory compatibility problems for the

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large warehouse and DC, which typically handle inventory for all industry sectors. For instance, an industry dealing with perishables definitely needs special inventory facilities. Last, from the cost angle, deploying RFID can reduce the cost by maintaining a reduced level of inventory, waste, manual checks, and other miscellaneous inventory handling and management costs.

Benefits to Logistics Company administration For company executives, RFID can improve administrative laboring. For example, RFID enables the fine-grained laboring productivity measurement by timing the uploading of the goods for particular workers. Moreover, RFID helps to avoid employee theft during the outbound shipping by identifying the nature of the items (goods or company property).

Benefits to Retailers For retailers, RFID can help to make the price strategy. This is achieved by employing the RFID readers that capture precise information on how much product was sold from each location by placing different RFID readers in different selling place (e.g., point-of-sale machines). Next, RFID can improve customer satisfaction since it provides the right information at the right time and in the right format. For instance, DHL and FedEx each use an RFID-enabled tracking service, which helps the customer to monitor its own consignment. Customer satisfaction is further improved when the RFID allows retailers to know exactly what products are available in stock and in what capacity, which prevents the customers from being disappointed under the circumstance that their desired products are out of stock.

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Benefits to the Whole Supply Chain For SCM strategists, RFID facilitates detailed data collection and statistical analysis, from gross to very fine-grained levels. For instance, RFID readers in a retailer’s store can capture data on product arrival, placement, and movement, which can present the cyclical patterns. This key capability of RFID allows the executives to link the date received with the date sold. Moreover, it can help to identify possible points of information leakage throughout the entire supply chain. As a result, RFID increases the visibility in the supply chain, which can be used to make strategic decisions to further increase competitive advantage.

adoptIon strategy In this section, we discuss the RFID adoption strategy, which facilitates the ultimate successful RFID deployment. In general, an adoption strategy provides a roadmap to implement the technology in a way that is consistent with an organization’s strategic vision and goal. It is our belief that such a road map comprises four essential fundamental principles for RFID to be thoroughly adopted in the organization. We formulate them as follows to guide the RFID adoption strategy.

shared understanding In an organization, each decision maker or potential stakeholder of the RFID adoption may have a considerably different understanding from his or her own perspective towards RFID. The likelihood of successful adoption of RFID in effect hinges on the capability of the organization to enforce a broader shared understanding. This calls for a harmonious integration of each individual’s opinion in a manner that benefits the organization’s core competency and strategic goal, rather than

that focuses on isolated areas of benefits. Hence, in the early stage, the main aim is to ensure that such a shared understanding is permeated at each level of the executive management and general administrative members of the organization.

goal setting No technology deployments can be successful unless the goals of the deployment program are aligned with the business goals. Hence, at the beginning of RFID adoption, the organization has to set a very clear unambiguous goal for RFID adoption. This goal is to be aligned with the organization’s existing business goal. With the goal, important stakeholders can thus be explicitly (rather than implicitly or potentially) identified. A definitive goal also helps to find the ‘buy-in’ among all the stakeholders of the RFID technologya key component in achieving organization change successfully due to the fact that support from senior management is exceptionally critical.

Justification It is well recognized that, in order to justify a new technology, a number of convincing business scenarios are of paramount importance. These scenarios must contribute to achieving the organization’s business goals. They can be substantiated by collecting and investigating all the operational and technical requirements in the organization. Moreover, a cost-benefit analysis (e.g., ROI estimation) to suffice the financial concern will significantly increase the possibility of RFID being accepted by those hesitant stakeholders. Last, potential challenges and issues during and after deploying RFID have to be clearly identified at the early stage. Each challenge should be addressed by possible solutions submitted to all involved stakeholders.

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Planning and Approaching Before starting the implementation, it is very important to define a detailed deployment plan with thorough consideration to various factors like schedule, impact, and usability. This facilitates a positive and quicker realization of the technology outcomes. A good project plan includes evaluation of technology option, standard-based deployment approach, measurements and optimization techniques, and a continuous improvement roadmap. During the implementation, an incremental approach shall be taken. Thus pilot tests and milestones can be used for checking the progress of the implementation and ensuring the desired outcome is achieved through the delta part implemented in the current adoption iteration. Based on these aforementioned principles, we then present a refined strategic step flow for the RFID adoption strategy. This is shown in Figure 5, where the elaborated steps (rectangles) of the roadmap are outlined one after another and are connected by directed edges and condition check (triangles). We explore each step one by one as follows.

Core Competency Reaffirmation The core competency (CC) is defined as one thing that an organization can do better than its competitors, and is crucial to its success. Before the organization adopts any candidate technologies, it has to assess them against the core competency. For example, if a new technology enables the organization to maintain its CC and even gain more CC (i.e., CC-aligned), then this technology is favorable to the organization and should be given further adequate consideration. Otherwise, such a technology needs more evaluation under current business contexts even if it appears very promising from the technical perspectives or from other organizations’ angles. It is highly desirable that the CC-aligned technology, once validated

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within the organization, receives unanimous support from senior management to the general staff. This undoubtedly paves the way for easier adoption that is less likely to be tangled with internal politics, funding difficulties, and some of the execution delays. For example, when retailer giant Wal-Mart realizes that the core competence lies in its dominant distribution channels, which can greatly benefit from RFID technology (as discussed above), it demands all of its top 100 suppliers to attach RFID tags onto their goods. On the contrary, if a company XYZ’s CC is manufacturing high-quality automobile engine assemblies, it should be very cautious in adopting RFID unless its primary retailers at the downstream urge it to do so, because the distribution is not XYZ’s core competencies and doing so will only distract itself from doing what they are good at. Therefore, in general, an organization should be wary of taking aggressive steps in implementing RFID solutions before the core competence has been thoroughly reaffirmed and evaluated.

Feasibility Analysis If the RFID technology is being considered to be aligned with the CC, it is time for the organization to perform the feasibility analysis, which deals with four major aspects: •

•

It is very important to estimate the capability of existing information systems. Since RFID will dramatically increase the amount of the data captured from instance level tags, the information systems have to capture, process, and analyze such a huge amount of data efficiently. Any insufficiency of information systems will definitely hinder the RFID technology to realize its full potential. RFID solutions could be quite costly; hence continuous and dedicated RFID funding support is essential.

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Figure 5. RFID adoption roadmap

Reaffirm the Core Competency (CC) of the business

P1 P2 P1

Prioritized Scenario List

For each candidate scenario RFID is aligned with CC?

Justification Review

Yes No Feasibility analysis 1. Information Sys. 2. Funding 3. Personnel 4. Time to deploy

Justified?

Adoption Issue Analysis

Feasible? Yes

Pilot Test and Result Analysis

Identify current candidate scenarios that might benefit from deploying

Yes Negative Impact? Continue

No Prioritize all the identified candidate scenarios against the estimated volume and rate of the return from RFID.

Implement this candidate scenario Milestone 1

Milestone 2

Milestone n

…… Prioritize candidate scenarios

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•

•

Personnel preparation is another feasibility issue needing consideration. Once implemented, the RFID might change the business process as well as fundamental information systems operations, which incur substantial IT training and adaptation study. The learning capability of involved working staff also determines the success of RFID adoption. Lastly, the organization has to choose the appropriate time to deploy RFID. Early adoption of RFID has advantages as well as risks. The feasibility of time should study whether the company is ready for RFID at that particular time, and moreover can bear the risk associated, even if the prerequisite conditions are all met.

Candidate Scenarios The next step is to identify candidate scenarios that would benefit from RFID and to measure the potential benefit in a self-defined scale. For example, for manufacturing units, RFID can be used to support quality control by querying components and subassemblies as they enter the facility. This is a typical candidate scenario that can be identified. It is recommended for the organization to enumerate all the potential RFIDinvolved candidate scenarios that can impact an organization’s core competences. One efficient way to accomplish such an enumeration would be to define several business areas based on the beneficiary summarized above (e.g., the manufacturing, distribution, warehouse management, etc.). For each business area, one representative candidate scenario is selected according to its relevance to the organization’s CC. Also, it is a good idea to break down a large scenario into a couple of smaller scenarios, and only one of which is chosen based on the stakeholders’ preferences (e.g., the one that promises the most effective impact towards the CC). In other words, as an emerging technology, RFID must be adopted in a selective and iterative manner so that the risk,

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cost, and organization changes can be controlled at the minimum level, whereas the positive impact to CC is pursued at the maximum level. A formal description is necessary to state the basic characteristics of each scenario. A typical tabular description of a sample candidate scenario (based on RosettaNet, 2001) is presented in Table 1.

Scenario Prioritization The previous step produces a list of candidate scenarios, each of which represents one particular business area in this organization. (Readers shall recall that one business area comprises a set of scenarios. For each iteration, we only choose one scenario from this set in each business area). In this step, we need to prioritize this list against a set of criteria such as estimated impacts to CC, the ROI, the cost, and so forth. Such a prioritizing process also needs to consider the preference from different RFID stakeholders. This is achieved by: 1. 2.

3. 4. 5.

6.

Organizing the criteria set into a hierarchical structure Performing the pair-wise comparison between any two candidate scenarios against one specific criterion Providing the pair-wise comparison between any two criteria for each rfid stakeholder Computing the stakeholders-aggregated preferences for each criteria Calculating the overall weight for each scenario allowing for all criteria with different preferences Ranking the scenario list against the weight value generated in #5, with the biggest weight value being positioned in the first rank. This step eventually generates a prioritized scenario list for further justification review.

Justification Review In this step, for each candidate scenario in the Prioritized Scenario List, the organization con-

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Table 1. A sample of candidate scenario Scenario Name: Involved Stakeholders:

Shipment Status Query 1.

A consignee, or third-party logistics firm, or shipper

2.

Consolidators, or warehousing entities, or freight forwarders, documentation personnel, carriers or custom clearing personnel

This scenario states a third-party logistics firm or shipper to query for the status

Scenario Description:

of one or more shipments and a transport service provider to respond to the query. Identifies the shipment for which status information is needed. The Shipper’s and Carrier’s Reference Numbers identify a particular shipment. Communicates

Detail Activities:

the status of a shipment. The Shipper’s and Carrier’s Reference Numbers identify a particular shipment. The response references geographical location, time, and customer’s entry number; it may include information about delivery exceptions. It does, if RFID technology is adopted, include order-level detail. Increasing the shipping data accuracy: • The transport service provider’s detailed shipping manifest ensures that the right number of cases is en route, thereby improving customer (e.g., consignee) service levels.

CC Impacts from RFID:

• The transport service provider reduces load times by eliminating manual order auditing. • There are fewer discrepancies between shipments and invoices, because the shipping manifest can automatically generate an invoice that includes case EPCs.

Business Process:

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ducts the justification review, a static analysis of RFID deployment only related to that particular candidate scenario. Readers are advised that several justification methods can be applied. For example, traditional ROI (return on investment) methods can be utilized to examine whether RFID technology should be deployed in this candidate scenario. However, they seem inadequate as RFID so far has a high level of uncertainty (e.g., tag prices, standards), and existing stories (eWeek. com) show that a number of possible applications are unfairly treated by existing ROI methods and tools. The appropriate justification tools are thus highly desirable and become a promising future research direction. For each candidate scenario, if the justification review produces negative results, it is removed from the prioritized scenario list, and the next scenario will be considered to perform the justification review. Otherwise, this scenario will be subsequently chosen for the following pilot test.

Adoption Issues Before the pilot test, a clear consensus of issues and their solutions is necessary among all the stakeholders. Hence in this step, the stakeholders need to unanimously identify adoption challenges specific to this scenario. The next section of this chapter will provide a comprehensive issue list that the organization should consider. However, we believe each scenario has its own unique set of adoption issues. Even for the same issue, it has different impact on various scenarios. It is suggested that the organization itemizes all the possible problems that it might encounter during the pilot test. More importantly, the solutions that address these challenges should be proposed and planned in this step. This ensures the smooth progress of the pilot test. Moreover, the solutions can also be validated and modified during the pilot test.

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Pilot Test Once the justification review is confirmed positively, the pilot implementation can be carried out in an experimental environment. It can be an RFID prototype in a smaller scope or scale of this candidate scenario. For example, a pilot deployment in one or two locations allows evaluation of RFID vendors, equipment, and software, and provides the opportunity for different stakeholders to gain experience with RFID. Furthermore, such a pilot is to produce the impact analysis for this candidate scenario. As many impacts can be associated with the RFID deployment, some of them are beneficial to some shareholders, while some are negative to other shareholders. Hence the pilot implementation can estimate such impacts brought by RFID deployment. If most of the results tend to be negative, the likelihood that the RFID to be implemented in this scenario appears to be very low. The organization might need to consider the next candidate scenario along the Prioritized Scenario List. In contrast, positive pilot test results with the pilot feedback suggest the start of the RFID implementation in this candidate scenario.

Implementation Once the pilot test is passed, the formal implementation can be carried out in an incremental manner through a set of iterations with a couple of milestones, which ensure that the implementation cost and risk can be controlled and mitigated to the minimal level. Each milestone has different focuses. Table 2 lists possible sequential tasks within one milestone. Particular attention is given for fostering the transition between milestones.

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Table 2. Sequential tasks within one milestone

Architecture Design

The architecture can follow some RFID reference model and must be extensible so that new architectural elements or scenarios can be added in the next milestones.

Edge Deployment

Assemble the RFID edge solution from selected vendors based on the drafted architecture rather than from one particular RFID system or product.

Verification and Validation

Measure the system performance and business impact.

Scale Deployment

Consider adding additional locations in terms of geography or business unit for next milestone.

Integration Deployment

Add the RFID data-integration middleware to enable the data sharing with other information systems, or even other partners. Consider adding business process integration infrastructure for the next milestone.

Evolve and Expand

Considering the adaptability of this milestone to ensure that it can expand and evolve to meet the changing needs of the business in the following milestones.

rfId adoptIon challenges Several key adoption issues will be discussed in this section. The main issues that we address in this section are cost associated with the deployment of RFID system, security and privacy concerns, and finally more technical issues in deployment of an RFID system.

cost A cost-estimation model for a full-fledged deployment of an RFID system in a supply chain environment should consider the following factors.

RFID Tags When deploying an RFID system, one should consider the cost of buying RFID tags. It is a good idea to consider renewable tags (if possible)

as a means to reduce cost. Normally the cost of active tags is more than the passive tags. The active tags are in the range of US$20 to $50 per tag (Lyngsoe, n.d.; RFID Journal, 2006a, 2006c) . The cost of the passive tags depends upon the frequency. Normally the LF tags are more expensive than HF or UHF because of the size of the antennae (RMOROZ, 2004). It normally costs more than $2 and goes as high as $10. The HF tags are cheaper than the LF tags and normally cost less than a dollar. Apart from the cost of the tags, companies should also consider the cost of testing the passive tags. The failure rate for the UHF EPC tags ranged from 0-20% in the year 2004. This might drop down once manufacturers start using sophisticated manufacturing techniques, however there is a cost associated to ensure that the tags are functioning properly. Finally there is cost associated with replacing the defective tags (RFID Journal, 2006c).

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RFID Printers

RFID Middleware

An RFID label has a similar functionality as an RFID tag. However it can be stuck on like a label. The RFID label can be printed using RFID printers. Hence if you are planning to use RFID labels, the cost of the RFID printer should be considered. In some applications RFID labels are much more preferred because of the environment and the products. For example applications like express parcel delivery, library book/video checkout, sensitive document tracking, ticketing (sports, concerts, ski lifts, etc.), and pharmaceuticals prefer RFID labels (Zebra, 2006).

RFID middleware contributes a major portion of RFID investment. Many vendors supply RFID middleware, and the cost can vary depending upon the capabilities of the middleware. Usually factors that contribute to cost include complexity of the application and the number of places the middleware would be installed. Apart from the middleware, the companies should also consider the cost of edge servers, which are normally deployed in the warehouse, distribution center, or production facility. The edge servers are simple servers, which are connected to the RFID reader using a universal serial bus (USB) port.

RFID Readers When deploying an RFID system, one should consider the cost of buying RFID readers. The fixed readers are normally cheaper than the portable readers. It is normally in the range of $500 to $5,000 depending on the features built into the reader (RFID Journal, 2006c). Dumb readers are usually cheaper, as they do not have any computing capability. On the other hand intelligent readers offer computing capability to filter data, store information, and execute commands. Agile readers can communicate with tags using a variety of protocols, while multi-frequency readers can read tags using different frequencies (RFID Journal, 2006c). All these features contribute to the cost of readers, and the organization should select a proper reader based on its application requirements.

RFID Antennas Almost all the readers are equipped with one or more antennas. However in some cases the need for additional high-power antennas cannot be ruled out, and hence this additional cost should be considered before deciding to deploy an RFID system.

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Training Existing Staff Introducing new technology in an organization introduces costs associated with training the concerned staff. For example an organization will need to train its employees, particularly engineering staff who will manage readers in manufacturing and warehouse facilities, and IT staff who will work on the systems that manage RFID data (RFID Journal, 2006c).

Hiring Technology Expertise Most of the companies, as of now, would not have the expertise to deploy a complete RFID system. This is partly attributed to the fact that RFID is a relatively new technology. Hence an organization would need to outsource this task to a third party who knows how to install the readers, decide the appropriate location for fixing the tag on the products, ascertain that the data gathered by the reader is properly propagated to the middleware in the right format, and so on. This is quite important because RFID systems can be sometimes difficult to install, as there are several factors that can affect the optimum performance of such a system. Hence a major portion of RFID investment has to be targeted to this area.

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Other Miscellaneous Costs

depending upon the number of distribution centers and warehouses in use. Here we assumed 100 readers and printers, and 50 edge servers. These numbers are used just as an example; it can vary depending upon each company.

The miscellaneous costs might include regular maintenance of the RFID readers or replacement of damaged tags or antennas.

Cost Estimation for RFID Deployment in Supply Chain Tracking

read-rate accuracy

When deploying an RFID system for inventory management and control in a supply chain, all the above-mentioned costs should be considered. According to Forrester Research, the estimated cost of middleware is around $183,000 for a $12 billion manufacturer looking to meet the RFID tagging requirements of a major retailer (RFID Journal, 2006c). In the same manner the estimated price of $128,000 could be spent for consulting and integration, $315,000 for the time of the internal project team, and $80,000 for tag and reader testing (RFID Journal, 2006c). A simple estimate is provided in Table 3. On the lower end an estimated cost of around $3 million should be invested in an RFID project for inventory tracking and management if a total of 10 million items are tagged. The number of readers, printers, and edge servers would vary

Achieving 100% read-rate accuracy is a major adoption challenge with RFID deployment. Supply chains and warehouse management solutions based on RFID are highly vulnerable to read-rate inaccuracy because of the number of RFID-tagged items that need to be scanned every second. Consider the scenario when a palette containing 1,000 RFID-tagged items is scanned at the warehouse exit. There is a high probability that the reader would not scan a few tags. It is difficult to list the main reasons that result in inaccurate readings because there are too many “ifs” and “buts”. Accuracy is dependent on so many unrelated variables that it is difficult to list the main factors behind the cause. However we attempt to outline some basic parameters, which results in inaccurate readings. Some of the main reasons for inaccurate readings include the environment in which RFID system works, material of the item

Table 3. Simple cost estimate Investment Area

No. of Units

Cost Per Unit (USD)

Total Cost (USD)

10,000,000

$ 0.15

$ 1,500,000.00

RFID Readers (Handheld, Fixed, Forklift)

100

$ 8,000.00

$ 800,000.00

RFID Printers

100

$ 3,000.00

$ 300,000.00

Edge Servers

50

$ 2,500.00

$ 125,000.00

RFID Tags

RFID Middleware

N.A.

$ 200,000.00

RFID Consulting

N.A.

$ 128,000.00

RFID Training

N.A.

Variable Cost

Tag Validation

N.A.

$ 80,000.00 Total Cost

$ 3,133,000.00

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being tracked, reader configuration, reader and tag placements, tag orientation, and so forth. To successfully deploy an RFID system, some key parameters should be considered to achieve accurate readings.

Tagged Material Maintain some consistency when tracking materials. It is not a good idea to standardize the reader configuration to track cartons, trolleys, pallets, glass materials, documents, or metal or plastic bins. This is because different materials behave differently to RF energy; some materials are RF friendly, while others are RF absorbent or RF opaque. A reader configured to read tags from RF-friendly material would definitely fail to give 100% read-rate accuracy if used to track RF-absorbent or RF-opaque items.

Preplanned Object Movement To assure good read rates, it is advised to move the tagged objects on a predefined route (or pattern). You cannot expect good rates if the cartons are moved through a forklift, people, metals trolleys, plastic trolleys, and so forth. There should be just one or two modes of transport well tested for 100% read-rate accuracy.

Tags from Different Vendors Read rate is also affected if tags are used from different vendors because the performance of such tags varies significantly. Another reason is the use of different standard-compliant tags (like EPC Gen1 & EPC Gen2). It is also difficult to configure the reader power level at an optimum level where it supports all different tags with 100% read rate. Ideally one should try to use a single standard and single vendor tag in one ecosystem. Nevertheless this may change as the standards improve.

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Tag Orientation Orientation is one of the big factors for providing good read rates. Even though dual dipole tags perform much better in all orientations, it is still advised to follow a policy on tag placement and tag orientation (TPTO). A standard policy on TPTO across an organization would definitely improve the read-rate accuracy.

security Security of RFID solutions in supply chain management is a major issue. Automated warehouse management and supply chain solutions based on RFID should leave no room for security loopholes. Security properties like confidentiality3, integrity4, availability5, authentication6, and anonymity7 need to be considered for the successful RFID adoption. Consider the warehouse management scenario: if a malicious reader can eavesdrop (spy) on the communication between the tags and the readers, confidentiality and anonymity in such communication is lost. A malicious reader may be placed by a competing organization to study the goods movement in your warehouse. Such tactics for gathering business intelligence can be addressed if security mechanisms are in place. Secondly, information stored on the RFID tag could also be tampered with by malicious readers, which could result in wrong items being loaded from the warehouse. For example, if the malicious reader changes the information on RFID tag from Orange to Apple, then a palette containing apples might be shipped when the intention was to ship oranges. Data tampering (or integrity) can raise issues like quality of service and trust in logistics and supply chain, and hence needs to be addressed thoroughly. Similarly, malicious entities can employ an active jamming approach to launch denial of service attacks, which would make the RFID network unavailable. In such an

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Figure 6. Major security issues with RFID adoption

Security Properties

Confidentiality

Availability

Authenticity

attack the RFID reader cannot query the tags, and hence the warehouse management system can stop working or real-time status of the warehouse cannot be made available (Engberg, Harning, & Jensen, 2004; Menezes, Van Oorschot, & Vanstone, 1996). In this section we discuss solutions from literature which can address these security issues. The details discussed in this section are explained from a security expert’s perspective. Hence if the reader is a business executive or management strategist, they may skip this section. All they need to know is that there are some security mechanisms in place (as shown in Figure 7) which can be used to guarantee security in communication between the tag and the reader. These security mechanisms are based on the assumption that expensive Gen-2 RFID tags are used.

Anonymity

Integrity

Access Control and Authentications Several approaches to access control and authentication are proposed in the literature. We will discuss some in greater detail in this section. Exclusive-OR Approach for Authentication A simple authentication scheme based on challenge-response protocol is presented in Juels, Rivest, and Szydlo (2003). It uses only simple bitwise exclusive-OR operations and no other complicated cryptographic primitives, hence it is suitable for RFIDs. However, the main issue with this approach, as pointed out by Dimitriou (2005), is that it involves the communication of four messages and frequent updates which would increase unnecessary traffic between the reader and the tag (Dimitriou, 2005; Wong & Phan, 2006). Feldhofer

Figure 7. Security solutions to address security issues with RFID adoption

Security Mechanisms

Access Control and Authentication

Tag Authentication

Encryption and Message Authentication

Tamper Detection

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(2004) demonstrated that it is possible to achieve authentication without making use of computationally intensive public-key cryptography, but instead used the advanced encryption standard (AES), which is a symmetric-key technique for encryption (Stallings, 1999; Vajda & Buttyan, 2003; Wong & Phan, 2006). Hash-based Approaches for Access Control A hash-based access control protocol is discussed in Weis (2003). Here the tag is first in a locked state. When the tag moves to the unlocked state, the reader can access the tag’s details. In order to change the state, the tag first transmits a meta ID, which is the hash value of a key. An authorized reader looks up the corresponding key in a backend system and sends it to the tag. The tag verifies the key by hashing it to return the clear text ID and remains only for a short time in an ‘unlocked’ state which provides time for reader authentication and offers a modest level of access security (Knospe & Pohl, 2004; Wong & Phan, 2006).

Tag Authentication Tag authentication is another security mechanism that authenticates the tag to the reader and protects against tag counterfeiting. There are several protocols proposed for this purpose. For example, Vajda and Buttyan (2003) propose and analyze several lightweight tag authentication protocols. Similarly, Feldhofer (2004) proposes the simple authentication and security layer (SASL) protocol with AES encryption and analyzes the hardware requirements (Feldhofer, 2004; Knospe & Pohl, 2004; Wong & Phan, 2006).

Encryption and Message Authentication Next-generation RFID systems like the ISO 14443 or MIFARE® offer encryption and authentication capability for data which is exchanged between the readers and the tags. In RFID systems the UID is the most important data, and this can be

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secured by encrypting the memory blocks at the application layer. The UID is usually read-only, and many RFID tags provide a permanent write lock of memory blocks. This can ensure data integrity, but of course, not message authentication (Knospe & Pohl, 2004; Wong & Phan, 2006).

Tamper Detection RFID tags carry data that represent the unique item identifier (UID) as well as product details to which it is attached. This data is very significant and, if tampered with, can have severe consequences. For example if data representing the “nature of good” is changed, it can have severe implicationthat is, instead of Lethal Weapons, the RFID could be modified to represent that the consignment carries Oranges. Such data tampering needs to be detected, as it can be a threat to national security. Potdar et al. (2005) presented a solution to address this security issue. They proposed a tamper-detection mechanism for low-cost RFID tags. The proposed algorithms for tamper detection works by embedding secret information (like a pattern) in the RFID tags. The pattern is embedded by manipulating the unique identifier in such a way that even after embedding the pattern, each RFID tag can be uniquely identified. To detect tampering, a tamper-detection component is introduced in the RFID middleware, which detects the embedded pattern. If the pattern is not present, it indicates data tampering, in which case the data from the RFID is quarantined and later processed appropriately (Potdar et al., 2005).

privacy The deployment of RFID in day-to-day life can raise several privacy concerns. The major concerns originate because of the inherent ability of RFID to track people who are using products that have RFID tags. Privacy experts say that marketers and retailers can gather detailed customer profiles, based on their transactions with that individual (Juels et al., 2003;

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Figure 8. Major privacy concerns with RFID adoption

Privacy Concerns

Analysing Consumer Behaviour

Cradle to Grave Surveillance

Discrimination

Kumar, n.d.) . The privacy concern originating by the use of RFID can be categorized into five areas as shown in Figure 8. If RFID is deployed in a full scale, it may result in many privacy concerns because RFID can be used to track consumer behavior, which can further be used to analyze consumer habits. It can even be used for hidden surveillance, for example, deploying secret RFIDs for tracking. With the size of RFIDs reducing day by day, it has now become possible to hide them within products without the owners’ consent. For example, RFID tags have already been hidden in packaging (Hennig, Ladkin, & Siker, 2005). A scenario of hidden RFID testing was discovered in a Wal-Mart store in Broken Arrow, Oklahoma, where secret RFID readers tracked customer action (Caspian, 2003). If RFIDs are embedded in money, it could result in discrimination. Consider this scenario: whenever a customer enters a shop equipped with RFID readers, they would easily know the purchasing power of the customer and can automatically manipulate pricing information to the customer’s credit worthiness. This results in automated prejudices (Hennig et al., 2005). Using RFIDs could even trigger anti-social activities. Criminals with RFID readers can look for people carrying valuable items and can launch selective attacks (Hennig et al., 2005). However most of these issues can be tackled by privacy enforcement laws, which can be incorporated into the nation’s legal framework. All these privacy issues

Terrorist Activities

Hidden Surveillance

have created a lot of fear in the consumer community. In order to address these issues, several approaches are proposed in the literature. We will discuss each of these techniques and then list the pros and cons of each approach.

Kill Tag Approach This is one of the simplest approaches to protect consumer privacy. According to this approach all the RFID tags would be killed or deactivated once they are sold to the customerthat is, when the products with the RFID tags pass through the checkout lane. Once a tag is killed, it can never be activated or used again. A password-protected ‘destroy’ command can also be integrated into the electronic product code (EPC) specifications, which would kill the tag permanently (Knospe & Pohl, 2004). However according to some privacy gurus, simple use of kill tag is sometimes inadequate. There are situations where the consumer would prefer the RFID tag to remain active even when the product is sold. For example, it would be wise to embed a tag in an airline ticket to allow simpler tracking of passengers within an airport. Consider embedding a tag in invoices, coupons, or return envelopes mailed to consumers; this can be used for ease of sorting upon return. Another example would be microwave ovens that read cooking instructions from food packages with embedded RFID tags (Kumar, n.d.). At the first instance, it seems that the kill tag approach would

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handle most of the privacy concerns, however as discussed above, in some situations it would be sensible to keep the tag active even after the product is sold. Hence this approach does not offer a satisfactory solution.

smartness of the tag. Many techniques to achieve privacy protection based on cryptographic protocols are proposed in the literature; some of these were already covered earlier in this chapter.

Physical Approach

case studIes

There are two basic approaches to achieve privacy protection using physical techniques. They are:

In this section we list a few RFID case studies from the supply chain and logistics domain.

•

Moraitis fresh

•

Faraday Cage Approach: A Faraday cage is an enclosure designed to exclude electromagnetic fields. As a result certain radio frequencies cannot penetrate through the enclosure area. It can address some privacy concerns, for example, if high-value currency notes start embedding a RFID tag, then using foil-lined wallets can guarantee privacy (Kumar, n.d.). This approach has limited application because a faraday cage cannot shield all items (mobile phones, clothing, etc). Active Jamming Approach: According to this approach the consumer can carry a radio device that would keep broadcasting radio signals in order to disrupt the normal operation of nearby RFID readers. Although this approach offers a way to protect privacy, it may be illegal in some countries. Broadcasting unnecessary radio signals can disrupt the operation of legitimate RFID readers where privacy is not concerned.

Smart Tag Approach This approach suggests making the RFID tags smarter so that they can manage the privacy concerns in much better manner. Adding extra functionality like introducing cryptographic capabilities would enable the tags to communicate in a secure environment and can increase the

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Moraitis supplies fresh fruits and vegetables to major supermarkets in Australia. The shelf life of such products is one or two weeks, which means the produce must be moved from the field to the supermarket within two to five days. Moraitis was looking at ways to boost the efficiency of its supply chain. IBM Business Consulting Services proposed an RFID solution for the above problem. Moraitis realized that RFID tags could offer a cost-effective solution to streamline supply chain functions, and help reduce the time and labor required. The technology was provided by Magellan’s StackTag technology, which can read and write to multiple tags moving on high-speed conveyors in any orientationeven when tags are overlapping or touching. The initial investment was around A$ 100,000. Automated inventory tracking improved the accuracy of Moraitis’ inventory management decisions (IBM, n.d.).

australia post Australia Post, the postal service in Australia, was looking at ways to improve its operational efficiency, focusing on a mail sorting problem. Lyngsoe Systems was approached to offer a solution. Australia Post has deployed Lyngsoe’s AMQM mail-quality measurement system, which contained more than 12,500 active tags (operating at 433.92 MHz frequency) and 400 RFID

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readers (Lyngsoe’s RD21 readers supporting 15 antennas) at several mail sorting and distribution locations. QSM software, which is an integral part of the AMQM system, is used to analyze RFID-generated mail-tracking data. The RFID readers will automatically read the tagged test envelopes as they pass through key sorting points in the network, and update the backend system (Collins, 2005).

australian Military The Australian Defense Force (ADF) had deployed an active RFID system for supply chain tracking to help forecast when shipments arrive at their destinations, and to ensure that material is accurately and efficiently ordered. Savi Technology deployed the RFID system, with an initial contract of US$10.1. The ADF deployed Savi’s SmartChain Consignment Management Solution (CMS), which is a suite of hardware and software components that uses barcode and RFID. ADF will now be able to make its logistics network more visible by using an in-transit visibility system (ITV) (O’Connor, 2005).

conclusIon Automated identification and data capture (AIDC) is a crucial technology in supply chain management as it forms the backbone of the modern supply chain. RFID, the emerging wireless AIDC technology, first appeared in tracking and access applications during the 1980s. It allowed for non-contact reading, and is very effective in manufacturing and other hostile environments where bar code labels could not survive. As a result the industry has looked into the possibility of embracing such a promising AIDC technology in a massive scale. Therefore, this chapter provided a comprehensive introduction to RFID technology and its application in supply chain

management from multi-level perspectives for various readersRFID novices, RFID advanced users, business consultants, business executives, scholars, and students. In particular, we first discussed fundamental RFID elements governed by specific RFID standards, which are further elaborated in detail. Having such basic knowledge, we identified RFID adoption challengesmainly cost, security, and privacywhich have become the biggest concern for those early RFID adopters. Bearing these big challenges in mind, company executives and management are seeking the roadmap of RFID deployment, which we offered as a dedicated section in this chapter. Before making substantial investment in RFID solutions, management would be interested in knowing existing successful case studies. We thus provided five RFID case studies to supplement this chapter for further references. All of these case studies are centered on logistics and supply chain domain, taking into consideration the overall theme of the book.

references Beherrschen, V. M. (n.d.). Frequency ranges. Retrieved February 2, 2006, from http://www. rfid-handbook.de/rfid/frequencies.html Caspian. (2003). Scandal: Wal-Mart, P&G involved in secret RFID testing. Retrieved June 13, 2006 from http://www.spychips.com/pressreleases/broken-arrow.html. Collins, J. (2005). Aussie track mail via RFID. Retrieved January 4, 2006, from http://www. rfidjournal.com/article/articleview/2014/1/1/ Dimitriou, T. (2005). A lightweight RFID protocol to protect against traceability and cloning attacks. In Proceedings of the Conference on Security & Privacy for Emerging Areas in Communication Networks.

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Engberg, S.J., Harning, M.B., & Jensen, C.D. (2004). Zero-knowledge device authentication: Privacy and security enhanced RFID preserving business value and consumer convenience. In Proceedings of the Conference on Privacy, Security & Trust (PST’04), Canada. eWeek.com. (n.d.). For many, RFID ROI still a dream. Retrieved June 10, 2006, from http://www. eweek.com/article2/0,1895,1756872,00.asp Feldhofer, M. (2004). A proposal for authentication protocol in a security layer for RFID smart tags. In Proceedings of the 12th IEEE Mediterranean Electrotechnical Conference (MELECON), Dubrovnik. Gloeckler, D. (n.d.). What is RFID? Retrieved September 1, 2005, from http://www.controlelectric.com/RFID/What_is_RFID.html Hennig, J.E., Ladkin, P.B., & Siker, B. (2005). Privacy enhancing technology concepts for RFID technology scrutinized. (Research Report # RVSRR-04-02) Bielefield: University of Bielefield. IBM. (n.d.). Moraitis fresh slices supply chain costs with IBM RFID solution. Retrieved January 8, 2006, from www.ibm.com/industries/wireless/ pdfs/moratis_final.pdf Intermec. (2006a). IF5 IntellliTag fixed reader. Retrieved June 14, 2006, from http://www.pointofsaleinc.com/pdf/Intermec/if5.pdf Intermec. (2006b). IP3 IntellliTag portable reader (UHF). Retrieved June 14, 2006, from http://www. pointofsaleinc.com/pdf/Intermec/ip3.pdf Intermec. (2006c). IV7 IntelliTag vehicle mount RFID reader. Retrieved June 14, 2006, from http:// www.pointofsaleinc.com/pdf/Intermec/iv7.pdf Juels, A., Rivest, R.L., & Szydlo, M. (2003). The blocker tag: Selective blocking of RFID tags for consumer privacy. In Proceedings of the 10th ACM Conference on Computer and Communications Security, Washington, DC.

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Knospe, H., & Pohl, H. (2004). RFID security information security technical report. Elsevier, 9(4), 30-41. Kumar, R. (n.d.). Interaction of RFID technology and public policy. Retrieved June 14, 2006, from http://www.wipro.com/distribution Leaver, S. (2005). Evaluating RFID middleware. Retrieved August 7, 2005, from http:// www.forrester.com/Research/Document/Excerpt/0,7211,34390,00.html Lyngsoe. (n.d.) Retrieved June 14, 2006, from http://www.lyngsoesystems.com Menezes, A., Van Oorschot, P., & Vanstone, S. (1996). Handbook of applied cryptography. London: CRC Press. O’Connor, M.C. (2005). Australia’s military to track supplies. Retrieved January 8, 2006, from http://www.rfidjournal.com/article/articleview/1838/1/1/ Potdar, V., Wu, C., & Chang, E. (2005, December 15-19). Tamper detection for ubiquitous RFID-enabled supply chain. In Proceedings of the International Conference on Computational Intelligence and Security, Xi’an, China. RFidGazzete. (n.d.). Tag shapes. Retrieved June 14, 2006, from http://www.rfidgazette. org/2005/10/tag_shapes.html RFID Journal. (2006a). Retrieved June 14, 2006, from http://www.rfidjournal.com/article/ articleview/208#Anchor-scanners-5989 RFID Journal. (2006b). Glossary results M-S. Retrieved June 14, 2006, from http://www.rfidjournal.com/article/glossary/3 RFID Journal. (2006c). RFID system components and costs. Retrieved February 13, 2006, from http://www.rfidjournal.com/article/articleview/1336/2/129/

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RMOROZ. (2004). Understanding radio frequency identification (RFID): Passive RFID. Retrieved June 14, 2006, from http://www.rmoroz. com/rfid.html RosettaNet. (2001). PIP™ specification— PIP3B4: Query shipment status. Retrieved June 14, 2006, from http://www.rosettanet.org Stallings, W. (1999). Cryptography and network security. Englewood Cliffs, NJ: Prentice-Hall.

Zebra. (2006). 13.56 MHz HF Zebra R-2844Z. Retrieved February 13, 2006, from http://www. zebra.com/id/zebra/na/en/index/products/printers/rfid.html

endnotes 1

2

Sweeney, P.J. (2005). RFID for dummies. Indianapolis, IN: Wiley Publishing. Symbol Technologies. (2004). Business benefits from radio frequency identification (RFID). Retrieved June 14, 2006, from http://www.symbol. com/products/rfid/rfid.html



3

Tecstra. (n.d.) RFID. Retrieved September 1, 2005, from http://glossary.ippaper.com/ Vajda, I., & Buttyan, L. (2003). Lightweight authentication protocols for low-cost RFID tags. In Proceedings of the 2nd Workshop on Security in Ubiquitous Computing (Ubicomp), Seattle, WA. Weis, S.A. (2003). Security and privacy in radiofrequency identification devices. Boston: Massachusetts Institute of Technology. Weis, S.A., Sarma, S.E., Rivest, R.L., & Engels, D.W. (2004). Security and privacy aspects of low-cost radio frequency identification systems. In Proceedings of Security in Pervasive Computing 2003. Wong, D.M.-L., & Phan, R.C.-W. (2006). RFID systems: Applications versus security & privacy implications. In G. Radhamani, & G.S.V. Radha Krishna Rao (Eds.), Web services security and ebusiness. Hershey, PA: Idea Group Publishing.

4

5

6

7

http://www.rfid-handbook.de/forum/read. php?f=4&i=81&t=81 RS-232 is a protocol for wired communication. Readers are connected using cables (max 30m) and the data transmission rate is very low. RS-485 is an improvement to RS-232, which still used cables, but can be large sized (1200m) and the data transmission rate is higher (2.5Mb per sec). Confidentiality refers to the confidentiality in communication between the tag and the reader. Integrity refers to the reliability of the information on the RFID tag. The RFID systems (in the UHF) work in a very congested frequency range; frequency jamming can easily attack such systems. Hence the availability of an RFID network is a security property which needs to be considered. One major security issue with the RFID tag is authentication. The data on the RFID tag like the unique identifier (UID) can be easily manipulated or spoofed, as these tags are not tamper resistant (Knospe & Pohl, 2004). Anonymity to undesired and anonymous scanning of items or people.

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Chapter 1.9

Contactless Payment with RFID and NFC Marc Pasquet GREYC Laboratory (ENSICAEN – Université Caen Basse Normandie - CNRS), France Delphine Vacquez ENSICAEN, France Joan Reynaud GREYC Laboratory (ENSICAEN – Université Caen Basse Normandie - CNRS), France Félix Cuozzo ENSICAEN, France

IntroductIon The radio frequency identification (RFID) reading technology enables the transfer, by radio, of information from electronic circuit to a reader, opened up some interesting possibilities in the area of epayment (Domdouzis, Kumar, & Anumba, 2007). Today, the near field communication technology (NFC) opens up even more horizons, because it can be used to set up communications between different electronic devices (Eckert, 2005).

Contactless cards, telephones with NFC capacities, RFID tag have been developed in industry and the services (Bendavid, Fosso Wamba, & Lefebvre, 2006). They are similar, but, some major differences explain the specificity of these three applications and the corresponding markets. The label, or marker, is a small size electronic element that transmits, on request, its numerical identification to a reader. The RFID identification makes it possible to store and recover data at short distance by using

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Contactless Payment with RFID and NFC

these miniature markers or labels (see Figure 1) associated to the articles to identify. The cost of the label is only few centimes. An RFID system is made of labels, readers connected to a fixed network, adapted software (collection of information, integration, confidentiality...), adapted services, and management tools that allow the identification of the products through packing. Contactless smartcards (see Figure 2) contain a microprocessor that can communicate under a short distance with a reader similar to those of RFID technology (Khu-smith & Mitchell, 2002). The originality of NFC is the fact that they were conceived for the protected bilateral transmission with other systems. NFC respects the standarda ISO-14443 (Bashan, 2003) and thus, can be used as a contactless card. It can be used as a contactless terminal communicating with a contactless card or another NFC phone (ISO-18092). Services available through NFC are very limited today, but many experiments are in progress and electronic

ticketing experiences (subways and bus) started in Japanb. There are two types of NFC phones: •

•

The mono chip composed of only one chip for GSM services (called the SIM) and NFC services. In that case, an NFC service is dependent of the phone operator. The dual chip shows a clear separation of the two functions within two different chips. That completely isolates the operator and allows independent NFC services…

We define the technology standards, the main platforms and actors in the background section. The main trust develops some contactless payment applications, and analyses the benefits and constraints of the different solutions. The future trends section concerns the research and technology evolution in contactless payment applications.

background Figure 1. Some examples of RFI label The major interest of contactless cards is to facilitate access control, micropayment… Another interest refers to the usury of card; it is insensible to contact oxidation. We detail briefly the international standards that are involved in RFID and NFC.

standards ISO-14443 Figure 2. Example of a contactless bank card This standard is the international one for contactless smartcards operating at 13.56 MHz in close proximity of a reader antenna. This ISO norm sets communication standards and transmission protocols between a card and a reader to create interoperability for contactless smartcard products. Two main communication protocols are supported under the ISO-14443 standard: Type

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A and B. Other protocols were only formalized: Type C (Sony/Japan), Type D (OTI/Israel), Type E (Cubic/USA), Type F (Legic/Switzerland). This norm is divided in four parts and treats Type A and Type B cards: •

•

•

•

ISO-14443-1 defines the size and physical characteristics of the antenna and the microchip; ISO-14443-2 defines the characteristics of the fields to be provided for power and bi-directional communication between coupling devices and cards; ISO-14443-3 defines the initialization phase of the communication and anticollision protocols; ISO-14443-4 specifies the transmission protocol.

ISO-14443 uses different terms to name its components: • •

PCD: proximity coupling device (or reader); PICC: proximity integrated circuit card (or contactless card).

ISO-18092 NFC is a short-range (10 to 20 centimeters) wireless communication technology that enables the Figure 3. The two NFC communication modes

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exchange of data between devices over a short distance. Its primal goal is the mobile phones usage. This open platform technology is standardized in ISO-18092 norm NFC Interface protocol-1c. In NFC technology, two communication modes exist: passive and active communication modes of NFC interface protocol to realize a communication network using NFC devices for networked products and also for consumer equipments (see Figure 3).

ISO-21481 The ISO-21481 standard (NFC interface protocol2d) is derived from Ecma-356 (interconnection) standard. It specifies the selection mechanism of communication mode in order to not disturb communication between devices using ISO-18092, ISO-14443 (contacless interface - proximity), and ISO-15693 (contacless interface - vicinity).

Application Platforms and Major actors There are major actors in the field of contactless applications; we distinguish two important platforms using the contactless technology: Mifare and FeliCa. This chapter does not focus on more details about these platforms technology, but is more about their applications.

Contactless Payment with RFID and NFC

Figure 4. Payment with a contactless card

MaIn focus of the chapter The main focus of the chapter is an analysis of the benefits and limitations of RFID authentication for electronic payment (Tajima, 2007). This part deals with the particular constraints of banking (computation time, security…) for this kind of authentication process (Chen & Adams, 2004). The use of radio frequency and the small distance allows some security weakness that leads to security reinforcements.

contactless cards in banking Applications Current actors in payment applications, namely MasterCard and Visa, stay alert, and intend to play a major role in future payment applications. They have already joined the movement and launch many developments over contactless payments. They begin to agree to a common communications protocol for contactless payment devices. This is based on the MasterCard PayPass™ protocol. MasterCard made the first step with a contactless credit card (see Figure 4) (Olsen, 2007). The Visa PayWave technology is rather largely deployed within many European countries. They both intended the American market to future deployments (Turner, 2006). Visa and MasterCard technologies comply with the EMV (Europay Mastercard Visa) standard. This standard defines the interoperation between smartcards and terminals for authenticating credit and debit cards. It defines strong security measures and provides a strong authentication along the process. Mobile specifications are still in an early stage of development. Those who want to follow the development can do it at the EMVCo Web sitee. Contactless cards that define the EMV standard over contactless communication does not differ so much with contact cards. The differences will be in the usages and applications.

We have seen that MasterCard and Visa have an agreement to share a common transmission protocol and experimentation for the contactless payments by radio frequency in the points of sale. Contactless payments, as conceived in the programs MasterCard PayPass and Visa PayWavef, make it possible for the cardholders to carry out fast payments by a simple passage of their card in front of a terminal, thus, avoiding them giving their payment card to a merchant or handling cash. Contactless payments are much more practical for the consumers and are particularly adapted in environments of purchase where the speed is essential, like fast food, the gas station, but also theaters. They also offer new appropriate payments by using a card in unusual environments of purchase, like slot-machines or tolls. To make a payment, a user presents his/her card near the front of a terminal (a beep is emitted by the terminal). A request for an online authorization is sent. The payment is carried out. There exist two types of PayPass cards: • •

Contactless with a magnetic stripe ; Contactless with a chip that is EMV compliant (dual-use card).

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Contactless Payment with RFID and NFC

For the European market, Visa is planning on using RFID-enabled dual-use debit cards, based on its own Visa Contactless payment technology. It aims, in particular, at European countries already using EMV compliant cards. But, Visa is also understood to be in talks with mobile manufacturers to use NFC technology that will enable a phone to be used instead of a card. For the US market, the contactless PayPass is not EMV compliant, so, the target is to limit the authorization requests (see Figure 5). How does it work? •

•

•

For a small amount (as for illustration