FreeDetector: Device-Free Occupancy Detection with Commodity WiFi

Abstract

Occupancy detection is playing a critical role to improve the efficiency of building management system and optimize personalized thermal comfort, among many other emerging applications. Conventional occupancy detection methods, such as Passive Infra-Red (PIR) and camera, have several drawbacks including low accuracy, high intrusiveness and extra infrastructure. In this work, we propose FreeDetector, a device-free occupancy detection scheme that is able to detect human presence accurately just using existing commodity WiFi routers. We upgrade the firmware of the routers so that the channel state information (CSI) data in PHY layer can be obtained directly from them. With only two routers, FreeDetector is able to reveal the variations in CSI data caused by human presence. We leverage signal tendency index (STI) to analyze the shape similarity of adjacent time series CSI curves. The most representative subset of subcarriers is selected by greedy algorithm and we utilize machine learning algorithm to construct a detection classifier. Extensive experiments are conducted and the results demonstrate that FreeDetector is able to provide outstanding occupancy detection service in terms of both accuracy and efficiency.