Smart Home Monitoring System via Footstep-Induced Vibrations

Instead of using traditional intrusive surveillance technologies such as cameras or body sensors, we propose a smart home system sensing the footstep-induced vibrations to feature the same functions which can be used for the assisted-living purpose. Based on distributed sensing and processing units, we adopt a distributed computing approach to preprocess the time-series data, recognize footstep signals, and extract vibration features locally. Through communications over the sensor networks, our system is capable to estimate the occupancy via counting the number of occupants. Besides, based on the multicomponent seismometer sensing system, we propose a novel indoor footstep localization method called angle constrained time difference of arrivals relying on both angle and arrival information of the recorded waveforms. According to separated pedestrian locations, different trajectories of multiple people can be tracked. From the location-tracking history, the resident's daily activities and social interactions can be inferred. In our experiments, the proposed system obtains promising results. Specifically, the location error is 0.14 m with a 0.11 m standard deviation. And the multipeople identification accuracy is above 87.83%.