research-article

Recognizing daily activities with RFID-based sensors

Authors:

Michael Buettner,

Matthai Philipose,

David WetherallAuthors Info & Claims

UbiComp '09: Proceedings of the 11th international conference on Ubiquitous computing

Pages 51 - 60

https://doi.org/10.1145/1620545.1620553

Published: 30 September 2009 Publication History

Abstract

We explore a dense sensing approach that uses RFID sensor network technology to recognize human activities. In our setting, everyday objects are instrumented with UHF RFID tags called WISPs that are equipped with accelerometers. RFID readers detect when the objects are used by examining this sensor data, and daily activities are then inferred from the traces of object use via a Hidden Markov Model. In a study of 10 participants performing 14 activities in a model apartment, our approach yielded recognition rates with precision and recall both in the 90% range. This compares well to recognition with a more intrusive short-range RFID bracelet that detects objects in the proximity of the user; this approach saw roughly 95% precision and 60% recall in the same study. We conclude that RFID sensor networks are a promising approach for indoor activity monitoring.

References

[1]

R. Aipperspach, E. Cohen, and J.F. Canny. Modeling human behavior from simple sensors in the home. In Pervasive, pages 337--348, 2006.

Digital Library

[2]

J.E. Bardram and H.B. Christensen. Pervasive computing support for hospitals: An overview of the activity-based computing project. IEEE Pervasive Computing, 6(1):44--51, 2007.

Digital Library

[3]

J. Beaudin, S.S. Intille, E.M. Tapia, R. Rockinson, and M.E. Morris. Context-sensitive microlearning of foreign language vocabulary on a mobile device. In Ambient Intelligence, volume 4794 of Lecture Notes in Computer Science, pages 55--72. Springer, 2007.

Digital Library

[4]

J.A. Bilmes. The GMTK documentation. http://ssli.ee.washington.edu/~bilmes/gmtk.

[5]

A.F. Bobick, S.S. Intille, J.W. Davis, F. Baird, C.S. Pinhanez, L.W. Campbell, Y.A. Ivanov, A. Schütte, and A.D. Wilson. The kidsroom. Communications of the ACM, 43(3):60--61, 2000.

Digital Library

[6]

M. Buettner, B. Greenstein, A. Sample, J.R. Smith, and D. Wetherall. Revisiting smart dust with rfid sensor networks. In Proc. Hot Topics in Networks (HotNets), 2008.

[7]

M. Buettner and D. Wetherall. An empirical study of UHF RFID performance. In Proc. Mobicom, 2008.

Digital Library

[8]

H.J. Chae, D.J. Yeager, J.R. Smith, and K. Fu. Maximalist cryptography and computation on the wisp uhf rfid tag. In Proc. Conference on RFID Security, 2007.

[9]

A. Czeskis, K. Koscher, J.R. Smith, and T. Kohno. Rfids and secret handshakes: Defending against ghost-and-leech attacks and unauthorized reads with context-aware communications. In 15th ACM Conference on Computer and Communications Security, 2008.

Digital Library

[10]

EPCglobal. Low level reader protocol (llrp), version 1.0.1. 2007.

[11]

K.P. Fishkin, M. Philipose, and A.D. Rea. Hands-on rfid: Wireless wearables for detecting use of objects. In ISWC, pages 38--43, 2005.

Digital Library

[12]

K.Z. Haigh, L.M. Kiff, and G. Ho. The Independent LifeStyle AssistantTM (I.L.S.A.): Lessons Learned. Assistive Technology, 2006.

[13]

S. Hodges, A. Thorne, H. Mallinson, and C. Floerkemeier. Assessing and optimizing the range of uhf rfid to enable real-world pervasive computing applications. In Lecture Notes in Computer Science -- Pervasive Computing, volume 4480, pages 280--297, 2007.

Digital Library

[14]

J. Holleman, D. Yeager, R. Prasad, J. Smith, and B. Otis. Neuralwisp: An energy-harvesting wireless neural interface with 1-m range. In BioCAS 2008, pages 37--40, Nov. 2008.

[15]

J. Lundell, T. Hayes, S. Vurgun, U. Ozertem, J. Kimel, J. Kaye, F. Guilak, and M. Pavel. Continuous activity monitoring and intelligent contextual prompting to improve medication adherence. In EMBS, pages 6286--6289, Aug. 2007.

[16]

M. Philipose, K. Fishkin, M. Perkowitz, D. Patterson, D. Fox, H. Kautz, and D. Hahnel. Inferring activities from interactions with objects. Pervasive Computing, IEEE, 3(4):50--57, Oct.-Dec. 2004.

Digital Library

[17]

M. Philipose, J. Smith, B. Jiang, A. Mamishev, S. Roy, and K. Sundara-Rajan. Battery-free wireless identification and sensing. Pervasive Computing, IEEE, 4(1):37--45, Jan.-March 2005.

Digital Library

[18]

A.P. Sample, D.J. Yeager, P.S. Powledge, and J.R. Smith. Design of an rfid-based battery-free programmable sensing platform. In IEEE Transactions on Instrumentation and Measurement, 2008.

[19]

J.R. Smith, A.P. Sample, P. Powledge, A. Mamishev, and S. Roy. A wirelessly powered platform for sensing and computation. In Proc. Ubicomp, 2006.

Digital Library

[20]

M.B. Srivastava, R.R. Muntz, and M. Potkonjak. Smart kindergarten: sensor-based wireless networks for smart developmental problem-solving enviroments. In MOBICOM, pages 132--138, 2001.

Digital Library

[21]

E.M. Tapia, S.S. Intille, and K. Larson. Activity recognition in the home using simple and ubiquitous sensors. In Pervasive, pages 158--175, 2004.

[22]

ThingMagic. Mercury4 rfid reader. http://www.thingmagic.com/fixed-rfid-readers/mercury4/2-fixed-rfid-readers/22-mercury4.

[23]

ThingMagic. Mercury5e rfid reader. http://www.thingmagic.com/embedded-rfidreaders/mercury5e.

[24]

D. Tse and P. Viswanath. Fundamentals of Wireless Communication. Cambridge University Press, 2005.

Digital Library

[25]

J. Ward, P. Lukowicz, G. Tröster, and T. Starner. Activity recognition of assembly tasks using body-worn microphones and accelerometers. IEEE Trans. Pattern Analysis and Machine Intelligence, 28(10):1553--1567, October 2006.

Digital Library

[26]

M. Weiser. The computer for the twenty-first century. Scientific American, 265(3):95--104, September 1991.

[27]

D.H. Wilson and C.G. Atkeson. Simultaneous tracking and activity recognition (STAR) using many anonymous, binary sensors. In Pervasive, pages 62--79, 2005.

Digital Library

[28]

D. Yeager, R. Prasad, D. Wetherall, P. Powledge, and J. Smith. Wirelessly-charged uhf tags for sensor data collection. In Proc. IEEE RFID, 2008.

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Li KIravantchi YZhu YPark HSample A(2025)HandSAW: Wearable Hand-based Event Recognition via On-Body Surface Acoustic WavesProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/37122769:1(1-29)Online publication date: 3-Mar-2025
https://dl.acm.org/doi/10.1145/3712276
Kim C(2024)Transforming Everyday Objects into IoT Control Interfaces: Design and Evaluation of the 'e-Rings' SystemArchives of Design Research10.15187/adr.2024.11.37.5.2937:5(29-49)Online publication date: 30-Nov-2024
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Index Terms

Recognizing daily activities with RFID-based sensors
1. Human-centered computing

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Published In

cover image ACM Conferences

UbiComp '09: Proceedings of the 11th international conference on Ubiquitous computing

September 2009

292 pages

ISBN:9781605584317

DOI:10.1145/1620545

General Chair:
Sumi Helal
University of Florida, USA
,
Program Chairs:
Hans Gellersen
Lancaster University, UK
,
Sunny Consolvo
Intel Labs, USA

Copyright © 2009 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 30 September 2009

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Ubicomp '09: The 11th International Conference on Ubiquitous Computing

September 30 - October 3, 2009

Florida, Orlando, USA

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UbiComp '09 Paper Acceptance Rate 31 of 251 submissions, 12%;

Overall Acceptance Rate 764 of 2,912 submissions, 26%

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Cited By

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https://dl.acm.org/doi/10.1145/3712276
Kim C(2024)Transforming Everyday Objects into IoT Control Interfaces: Design and Evaluation of the 'e-Rings' SystemArchives of Design Research10.15187/adr.2024.11.37.5.2937:5(29-49)Online publication date: 30-Nov-2024
https://doi.org/10.15187/adr.2024.11.37.5.29
Wang XZhang Y(2024)TextureSightProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36314137:4(1-27)Online publication date: 12-Jan-2024
https://dl.acm.org/doi/10.1145/3631413
Sepahvand MMeqdad MAbdali-Mohammadi F(2024)State-of-the-art in human activity recognition based on inertial measurement unit sensors: survey and applicationsInternational Journal of Computers and Applications10.1080/1206212X.2024.242650147:1(1-16)Online publication date: 18-Nov-2024
https://doi.org/10.1080/1206212X.2024.2426501
Yang XSayono JZhang Y(2023)CubeSense++: Smart Environment Sensing with Interaction-Powered Corner Reflector MechanismsProceedings of the 36th Annual ACM Symposium on User Interface Software and Technology10.1145/3586183.3606744(1-12)Online publication date: 29-Oct-2023
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Huang XMiller KSample ABanovic N(2023)StructureSenseProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35703436:4(1-25)Online publication date: 11-Jan-2023
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Li SLi SChen MSong CLu L(2023)Frequency Scaling Meets Intermittency: Optimizing Task Rate for RFID-Scale Computing DevicesIEEE Transactions on Mobile Computing10.1109/TMC.2023.3239515(1-12)Online publication date: 2023
https://doi.org/10.1109/TMC.2023.3239515
Li YTong XRen QLi QYang LChen YXue GJi XYu J(2023)AUDIOSENSE: Leveraging Current to Acoustic Channel to Detect Appliances at Single-Point2023 20th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)10.1109/SECON58729.2023.10287491(240-248)Online publication date: 11-Sep-2023
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Xu HYin XZhu FLi P(2023)RF-Ray: Sensing Objects in the Package via RFID SystemsIEEE Systems Journal10.1109/JSYST.2022.319646217:1(558-568)Online publication date: Mar-2023
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Lankipalli VYogeswari AArchana JSridevi SSridhar NPappa M(2023)Arduino based Smart Controller for Footwear Mat2023 5th International Conference on Smart Systems and Inventive Technology (ICSSIT)10.1109/ICSSIT55814.2023.10060932(440-445)Online publication date: 23-Jan-2023
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