Device-free multiple people localization through floor vibration

Abstract

Structural vibration-based human sensing provides an alternative approach for device-free human monitoring, which is used for healthcare, space and energy usage management, etc. Prior work on this approach mainly focused on one person walking scenarios, which limits their widespread application. The challenge with multiple walkers is that the observed vibration response is a mixture of each walker's footstep-induced response, and it is difficult to identify 1) how many concurrent walkers are present, and 2) the timing of their footstep impacts on the floor. As a result, the extraction of detailed location information for each walker is erroneous. To address this challenge, we propose a structure-informed vibration signal characterization method to enable the detection and localization of overlapping vibration signals induced by multiple concurrent walkers. The intuition is that, due to the randomness in people's behavior, their footsteps do not impact the floor exactly at the same time and overlap partially. We decompose the signal to a non-fundamental frequency band which contains the heel strike onset information. With this decomposed signal, we can identify the number of walkers and use the initial peak information to localize each person independently. We conducted real-world experiments with up to three concurrent walkers and our system achieved a detection rate of up to 90% and an average localization error of 0.65m (2.9X baseline improvement).