Device-free Human Tracking and Gait Recognition Based on the Smart Speaker

The smart speakers benefit from the ability to localize and identify users. Specifically, we can analyze the user's habits from the historical trajectory to provide better voice-based services. However, current voice localization method requires the user to actively issue voice commands, which makes smart speakers unable to track and identify silent users most of the time. This paper introduces WSTrack+, a system that combines W i-Fi and S ound to track human movement and recognize gait patterns. In particular, current smart speakers naturally support both Wi-Fi and acoustic functions. As a result, we are able to construct the system using just one router and a smart speaker, which is a more promising approach compared to existing systems that rely on multiple routers for sensing. To track and identify the silent user, our insights are twofold: 1) the smart speakers can hear the sound of the user's footstep, and then extract which direction the user is in; 2) we can extract the reflected path change rate from the Wi-Fi signals, and the acoustic signal can help us convert the path change rate into the actual user's velocity. Our implementation and evaluation on commodity devices demonstrate that WSTrack+ can realize simultaneous tracking and gait recognition, where the median tracking error is 0. 34m and the recognition accuracy is 88. 6% for 12 users.