Enabling Noninvasive Physical Assault Monitoring in Smart School with Commercial Wi-Fi Devices

Abstract EN

Monitoring physical assault is critical for the prevention of juvenile delinquency and promotion of school harmony.

A large portion of assault events, particularly school violence among teenagers, usually happen at indoor secluded places.

Pioneering approaches employ always-on-body sensors or cameras in the limited surveillance area, which are privacy-invasive and cannot provide ubiquitous assault monitoring.

In this paper, we present Wi-Dog, a noninvasive physical assault monitoring scheme that enables privacy-preserving monitoring in ubiquitous circumstances.

Wi-Dog is based on widely deployed commodity Wi-Fi infrastructures.

The key intuition is that Wi-Fi signals are easily distorted by human motions, and motion-induced signals could convey informative characteristics, such as intensity, regularity, and continuity.

Specifically, to explicitly reveal the substantive properties of physical assault, we innovatively propose a set of signal processing methods for informative components extraction by selecting sensitive antenna pairs and subcarriers.

Then a novel signal-complexity-based segmentation method is developed as a location-independent indicator to monitor targeted movement transitions.

Finally, holistic analysis is employed based on domain knowledge, and we distinguish the violence process from both local and global perspective using time-frequency features.

We implement Wi-Dog on commercial Wi-Fi devices and evaluate it in real indoor environments.

Experimental results demonstrate the effectiveness of Wi-Dog which consistently outperforms the advanced abnormal detection methods with a higher true detection rate of 94% and a lower false alarm rate of 8%.