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.
@article{arxiv.1907.06005,
title = {BeSense: Leveraging WiFi Channel Data and Computational Intelligence for Behavior Analysis},
author = {Yu Gu and Xiang Zhang and Zhi Liu and Fuji Ren},
journal= {arXiv preprint arXiv:1907.06005},
year = {2020}
}
Comments
11 pages accepted by IEEE Computational Intelligence Magazine