Collaborative sensing for privacy preserving gait tracking using IoT Middleware

Chi Sheng Shih; Tim Yuao Wang; Jyun Jhe Chou; Ze Yu Chuang; Ching Chi Chuang; Kwei Jay Lin; Wei Dean Wang; Kuo Chin Huang

doi:10.1145/3129676.3129696

Collaborative sensing for privacy preserving gait tracking using IoT Middleware

Chi Sheng Shih, Tim Yuao Wang, Jyun Jhe Chou, Ze Yu Chuang, Ching Chi Chuang, Kwei Jay Lin, Wei Dean Wang, Kuo Chin Huang

National Taiwan University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

Abstract

Gait velocity has become a valid and important metric for senior populations. However, existing approaches to measure gait velocity are either limited to specific location or too expensive to be applied. IoT middleware allows the systems to collect data in a large space in a collaborative manner. However, it is a great challenge of integrating large numbers of low-cost devices to accomplish the task. This paper presents the design, implementation, and findings of using low-cost thermal sensors to monitor the activity index in home environment. The system is built on top of WuKong middleware. The evaluation results show that the system can measure the gait velocity with negligible errors. When the parameters for noise filtering are correctly configured, the F-Score of the heat source detection can achieve 0.99.

Original language	English
Title of host publication	Proceedings of the 2017 Research in Adaptive and Convergent Systems, RACS 2017
Publisher	Association for Computing Machinery, Inc
Pages	152-159
Number of pages	8
ISBN (Electronic)	9781450350273
DOIs	https://doi.org/10.1145/3129676.3129696
State	Published - 20 09 2017
Externally published	Yes
Event	2017 International Conference on Research in Adaptive and Convergent Systems, RACS 2017 - Krakow, Poland Duration: 20 09 2017 → 23 09 2017

Publication series

Name	Proceedings of the 2017 Research in Adaptive and Convergent Systems, RACS 2017
Volume	2017-January

Conference

Conference	2017 International Conference on Research in Adaptive and Convergent Systems, RACS 2017
Country/Territory	Poland
City	Krakow
Period	20/09/17 → 23/09/17

Bibliographical note

Publisher Copyright:
© 2017 Association for Computing Machinery.

Keywords

Computer Communication Networks
Computer Systems Organization
Internetworking

Access to Document

10.1145/3129676.3129696

Cite this

Shih, C. S., Wang, T. Y., Chou, J. J., Chuang, Z. Y., Chuang, C. C., Lin, K. J., Wang, W. D., & Huang, K. C. (2017). Collaborative sensing for privacy preserving gait tracking using IoT Middleware. In Proceedings of the 2017 Research in Adaptive and Convergent Systems, RACS 2017 (pp. 152-159). (Proceedings of the 2017 Research in Adaptive and Convergent Systems, RACS 2017; Vol. 2017-January). Association for Computing Machinery, Inc. https://doi.org/10.1145/3129676.3129696

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title = "Collaborative sensing for privacy preserving gait tracking using IoT Middleware",

abstract = "Gait velocity has become a valid and important metric for senior populations. However, existing approaches to measure gait velocity are either limited to specific location or too expensive to be applied. IoT middleware allows the systems to collect data in a large space in a collaborative manner. However, it is a great challenge of integrating large numbers of low-cost devices to accomplish the task. This paper presents the design, implementation, and findings of using low-cost thermal sensors to monitor the activity index in home environment. The system is built on top of WuKong middleware. The evaluation results show that the system can measure the gait velocity with negligible errors. When the parameters for noise filtering are correctly configured, the F-Score of the heat source detection can achieve 0.99.",

keywords = "Computer Communication Networks, Computer Systems Organization, Internetworking",

author = "Shih, {Chi Sheng} and Wang, {Tim Yuao} and Chou, {Jyun Jhe} and Chuang, {Ze Yu} and Chuang, {Ching Chi} and Lin, {Kwei Jay} and Wang, {Wei Dean} and Huang, {Kuo Chin}",

note = "Publisher Copyright: {\textcopyright} 2017 Association for Computing Machinery.; 2017 International Conference on Research in Adaptive and Convergent Systems, RACS 2017 ; Conference date: 20-09-2017 Through 23-09-2017",

year = "2017",

month = sep,

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doi = "10.1145/3129676.3129696",

language = "英语",

series = "Proceedings of the 2017 Research in Adaptive and Convergent Systems, RACS 2017",

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Shih, CS, Wang, TY, Chou, JJ, Chuang, ZY, Chuang, CC, Lin, KJ, Wang, WD & Huang, KC 2017, Collaborative sensing for privacy preserving gait tracking using IoT Middleware. in Proceedings of the 2017 Research in Adaptive and Convergent Systems, RACS 2017. Proceedings of the 2017 Research in Adaptive and Convergent Systems, RACS 2017, vol. 2017-January, Association for Computing Machinery, Inc, pp. 152-159, 2017 International Conference on Research in Adaptive and Convergent Systems, RACS 2017, Krakow, Poland, 20/09/17. https://doi.org/10.1145/3129676.3129696

Collaborative sensing for privacy preserving gait tracking using IoT Middleware. / Shih, Chi Sheng; Wang, Tim Yuao; Chou, Jyun Jhe et al.
Proceedings of the 2017 Research in Adaptive and Convergent Systems, RACS 2017. Association for Computing Machinery, Inc, 2017. p. 152-159 (Proceedings of the 2017 Research in Adaptive and Convergent Systems, RACS 2017; Vol. 2017-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Shih, Chi Sheng

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AU - Chuang, Ching Chi

AU - Lin, Kwei Jay

AU - Wang, Wei Dean

AU - Huang, Kuo Chin

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AB - Gait velocity has become a valid and important metric for senior populations. However, existing approaches to measure gait velocity are either limited to specific location or too expensive to be applied. IoT middleware allows the systems to collect data in a large space in a collaborative manner. However, it is a great challenge of integrating large numbers of low-cost devices to accomplish the task. This paper presents the design, implementation, and findings of using low-cost thermal sensors to monitor the activity index in home environment. The system is built on top of WuKong middleware. The evaluation results show that the system can measure the gait velocity with negligible errors. When the parameters for noise filtering are correctly configured, the F-Score of the heat source detection can achieve 0.99.

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Shih CS, Wang TY, Chou JJ, Chuang ZY, Chuang CC, Lin KJ et al. Collaborative sensing for privacy preserving gait tracking using IoT Middleware. In Proceedings of the 2017 Research in Adaptive and Convergent Systems, RACS 2017. Association for Computing Machinery, Inc. 2017. p. 152-159. (Proceedings of the 2017 Research in Adaptive and Convergent Systems, RACS 2017). doi: 10.1145/3129676.3129696

Collaborative sensing for privacy preserving gait tracking using IoT Middleware

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