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Open Access

WiSH: WiFi-Based Real-Time Human Detection

Tianmeng Hang†, Yue Zheng†, Kun Qian, Chenshu Wu, Zheng Yang( ), Xiancun Zhou, Yunhao Liu, Guilin Chen
School of Software and BNRist, Tsinghua University, Beijing 100084, China.
Department of Computer Science and Engineering, Michigan State Unversity, East Lansing, MI 48824, USA.
Department of Electrical & Computer Engineering, Univeristy of Maryland, College Park, MD 20742, USA.
School of Information Engineering, West Anhui University, Lu’an 237012, China.
School of Computer and Information Engineering, Chuzhou University, Chuzhou 239000, China.

† Tianmeng Hang and Yue Zheng contribute equally to this paper.

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Abstract

Sensorless 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, but they frequently omit various practical constraints such as real-time capability, computation efficiency, sampling rates, deployment efforts, etc. A practical detection system that works in real-world applications is lacking. 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 low signal sampling rates. We deploy WiSH on commodity desktops and customized tiny nodes in different everyday scenarios. The experimental results demonstrate the superior performance of WiSH, which has a detection accuracy of >98% using a sampling rate of 20 Hz with an average detection delay of merely 1.5 s.Thus, we believe WiSH is a promising system for real-world deployment.

Keywords

channel state informationhuman detectionreal-time systemwireless sensingoff-the-shelf WiFi

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Tsinghua Science and Technology
Volume 24 Issue 5,
October 2019
Pages 615-629
DOI: 10.26599/TST.2018.9010091
Cite this article:
Hang T, Zheng Y, Qian K, et al. WiSH: WiFi-Based Real-Time Human Detection. Tsinghua Science and Technology, 2019, 24(5): 615-629. https://doi.org/10.26599/TST.2018.9010091

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Received: 12 January 2018
Revised: 04 March 2018
Accepted: 10 March 2018
Published: 29 April 2019
© The author(s) 2019
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