Wi-Dog: Monitoring school violence with commodity WiFi devices

Abstract

Monitoring school violence is critical for the prevention of juvenile delinquency and promotion of social harmony. Pioneering approaches employ always-on-body sensors or cameras with limited surveillance area, which cannot provide ubiquitous violence monitoring. In this paper, we present Wi-Dog, a non-invasive physical violence monitoring scheme based on commodity WiFi infrastructures. The key intuition is that violence-induced WiFi signals convey informative characteristics of intensity, irregularity and continuity. To identify school violence from violence-alike actions (e.g., jump, lie down and run), we develop a precise noise reduction method by selecting sensitive antenna pair and subcarriers. Moreover, a wavelet-entropy-based segmentation method is proposed to detect movement transitions in the distance, and the complete local-global analysis is further adopted to improve overall performance. We implemented Wi-Dog using commercial WiFi devices and evaluated it in real indoor environments. Experimental results demonstrate the effectiveness of Wi-Dog with average detection accuracy of 0.9.