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Conference Paper: WiSH: The design and implementation of a real-time system for whole-day human detection

TitleWiSH: The design and implementation of a real-time system for whole-day human detection
Authors
KeywordsWireless Sensing
Channel State Information
Human Detection
Real-time System
Off-the-shelf WiFi
Issue Date2018
Citation
Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS, 2018, v. 2017-December, p. 89-96 How to Cite?
AbstractSensorless sensing using wireless signals has been rapidly conceptualized and developed recently. Among numerous applications of WiFi-based sensing, human presence detection acts as a primary and fundamental function to boost applications in practice. Many complicated approaches have been proposed to achieve high detection accuracy, which, however, frequently omit various practical constraints like real-time capability, computation efficiency, sampling rates, deployment efforts, etc. A practical detection system that works in real world lacks. In this paper, we design and implement WiSH, a real-time system for contactless human detection that is applicable for whole-day usage. WiSH employs lightweight yet effective methods and thus enables detection under practical conditions even on resource-limited devices with very low signal sampling rates. We deploy WiSH on commodity desktops and customized tiny nodes in different everyday scenarios. The experimental results demonstrate superior performance of WiSH, achieving a detection accuracy of >98% using a sampling rate of 20Hz with an average detection delay of merely 1.5s, which renders it a promising system for real-world deployment.
Persistent Identifierhttp://hdl.handle.net/10722/303563
ISSN
2020 SCImago Journal Rankings: 0.212
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorZheng, Yue-
dc.contributor.authorHang, Tianmeng-
dc.contributor.authorQian, Kun-
dc.contributor.authorWu, Chenshu-
dc.contributor.authorYang, Zheng-
dc.contributor.authorZhou, Xiancun-
dc.date.accessioned2021-09-15T08:25:34Z-
dc.date.available2021-09-15T08:25:34Z-
dc.date.issued2018-
dc.identifier.citationProceedings of the International Conference on Parallel and Distributed Systems - ICPADS, 2018, v. 2017-December, p. 89-96-
dc.identifier.issn1521-9097-
dc.identifier.urihttp://hdl.handle.net/10722/303563-
dc.description.abstractSensorless sensing using wireless signals has been rapidly conceptualized and developed recently. Among numerous applications of WiFi-based sensing, human presence detection acts as a primary and fundamental function to boost applications in practice. Many complicated approaches have been proposed to achieve high detection accuracy, which, however, frequently omit various practical constraints like real-time capability, computation efficiency, sampling rates, deployment efforts, etc. A practical detection system that works in real world lacks. In this paper, we design and implement WiSH, a real-time system for contactless human detection that is applicable for whole-day usage. WiSH employs lightweight yet effective methods and thus enables detection under practical conditions even on resource-limited devices with very low signal sampling rates. We deploy WiSH on commodity desktops and customized tiny nodes in different everyday scenarios. The experimental results demonstrate superior performance of WiSH, achieving a detection accuracy of >98% using a sampling rate of 20Hz with an average detection delay of merely 1.5s, which renders it a promising system for real-world deployment.-
dc.languageeng-
dc.relation.ispartofProceedings of the International Conference on Parallel and Distributed Systems - ICPADS-
dc.subjectWireless Sensing-
dc.subjectChannel State Information-
dc.subjectHuman Detection-
dc.subjectReal-time System-
dc.subjectOff-the-shelf WiFi-
dc.titleWiSH: The design and implementation of a real-time system for whole-day human detection-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/ICPADS.2017.00023-
dc.identifier.scopuseid_2-s2.0-85048364503-
dc.identifier.volume2017-December-
dc.identifier.spage89-
dc.identifier.epage96-
dc.identifier.isiWOS:000448853600012-

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