BeSense: Leveraging WiFi Channel Data and Computational Intelligence for Behavior Analysis

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 and affective computing. Traditional sensor-based and vision-based user behavior analysis approaches are obtrusive in general, hindering their usage in real-world. Therefore, in this article, we first introduce the 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. We prototype BeSense on commodity low-cost WiFi devices and evaluate its performance in real-world environments. Experimental results have verified its effectiveness in recognizing user behaviors.