BeSense: Leveraging WiFi Channel Data and Computational Intelligence for Behavior Analysis
July 13, 2019 Β· Declared Dead Β· π IEEE Computational Intelligence Magazine
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Authors
Yu Gu, Xiang Zhang, Zhi Liu, Fuji Ren
arXiv ID
1907.06005
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.AI,
eess.SP
Citations
34
Venue
IEEE Computational Intelligence Magazine
Last Checked
3 months ago
Abstract
The ever evolving informatics technology has gradually bounded human and computer in a compact way. Understanding user behavior becomes a key enabler in many fields such as sedentary-related healthcare, human-computer interaction (HCI) and affective computing. Traditional sensor-based and vision-based user behavior analysis approaches are obtrusive in general, hindering their usage in realworld. Therefore, in this article, we first introduce WiFi signal as a new source instead of sensor and vision for unobtrusive user behaviors analysis. Then we design BeSense, a contactless behavior analysis system leveraging signal processing and computational intelligence over WiFi channel state information (CSI). We prototype BeSense on commodity low-cost WiFi devices and evaluate its performance in realworld environments. Experimental results have verified its effectiveness in recognizing user behaviors.
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