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Research and application of human activity detection technology based on Wi-Fi sensing for home environment adaptation
- 1 FOSHAN VIOMI ELECTRICAL TECHNOLOGY CO.,LTD.
- 2 FOSHAN VIOMI ELECTRICAL TECHNOLOGY CO.,LTD.
- 3 FOSHAN VIOMI ELECTRICAL TECHNOLOGY CO.,LTD.
- 4 FOSHAN VIOMI ELECTRICAL TECHNOLOGY CO.,LTD.
* Author to whom correspondence should be addressed.
Abstract
In the context of the progressive development of integrated communication and sensing technology, indoor motion detection relying on Wi-Fi Channel State Information (CSI) has attracted significant attention within the industry [1][2][3]. Nevertheless, the home environment presents several challenges that impinge on the reliability of CSI. These challenges include interference [4], intricate spatial arrangements, and the instability of device placement. Moreover, motion sensing based on the CSI paths between terminals and routers may encounter problems such as unpredictable effective ranges [5] and difficulties in penetrating walls. To surmount these obstacles, this paper proposes the following technologies: a) adaptive Signal-to-Noise Ratio (SNR) enhancement; b) adversarial sample training; c) a method for refining spatial granularity; and d) a lightweighting approach for edge-side models. These technologies enable the detection of region-specific human activities through Wi-Fi CSI. The experimental findings demonstrate a reduction in false detection rates and the successful implementation of deep-learning models on compact communication equipment.
Keywords
Wi-Fi sensing, Channel State Information, indoor motion detection, edge AI
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Cite this article
Zhang,F.;Huang,X.;Chen,Z.;Duan,E. (2025). Research and application of human activity detection technology based on Wi-Fi sensing for home environment adaptation. Advances in Engineering Innovation,16(2),44-60.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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