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Communications and Networking. 14th EAI International Conference, ChinaCom 2019, Shanghai, China, November 29 – December 1, 2019, Proceedings, Part II

Research Article

T-HuDe: Through-The-Wall Human Detection with WiFi Devices

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  • @INPROCEEDINGS{10.1007/978-3-030-41117-6_16,
        author={Wei Zeng and Zengshan Tian and Yue Jin and Xi Chen},
        title={T-HuDe: Through-The-Wall Human Detection with WiFi Devices},
        proceedings={Communications and Networking. 14th EAI International Conference, ChinaCom 2019, Shanghai, China, November 29 -- December 1, 2019, Proceedings, Part II},
        proceedings_a={CHINACOM PART 2},
        year={2020},
        month={2},
        keywords={Through-The-Wall Active human detection Channel State Information},
        doi={10.1007/978-3-030-41117-6_16}
    }
    
  • Wei Zeng
    Zengshan Tian
    Yue Jin
    Xi Chen
    Year: 2020
    T-HuDe: Through-The-Wall Human Detection with WiFi Devices
    CHINACOM PART 2
    Springer
    DOI: 10.1007/978-3-030-41117-6_16
Wei Zeng1,*, Zengshan Tian1, Yue Jin1, Xi Chen1
  • 1: Chongqing Key Lab of Mobile Communications Technology, School of Communication and Information Engineering
*Contact email: zengweicq@gmail.com

Abstract

With the rapid development of emerging smart homes applications, the home security systems based on passive detection without carrying any devices has been increasing attention in recent years. Through-The-Wall (TTW) detection is a great challenge since through-the-wall signal can be severely attenuated, and some of the existing TTW-based detection techniques require special equipment or have strict restrictions on placement of devices. Due to the near-ubiquitous wireless coverage, WiFi based passively human detection technique becomes a good solution. In this paper, we propose a robust scheme for device-free Through-the-wall Human Detection (T-HuDe) in TTW with Channel State Information (CSI), which can provide more fine-grained movement information. Especially, T-HuDe utilizes motion information on WiFi signal and uses statistical information of motion characteristics as parameters. To evaluate T-HuDe performance, we prototype it in different environments with commodity devices, and the test results show that human activity detection rate and human absence detection rate of T-HuDe are both above 93% in most detection areas.

Keywords
Through-The-Wall Active human detection Channel State Information
Published
2020-02-27
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-41117-6_16
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