Towards the Detection and Localization of Multiple Occupant Footsteps from Vibroacoustic Measurements

Tracking occupants indoors has important applications such as intruder detection and tracking. It has been shown that a vibration measurement system of underfloor accelerometer sensor network can detect, localize, and track occupants in a non-intrusive manner. In the literature, little attention has been given to studying the problem of detecting occupant foot-fall impacts in a real-life scenario, and its effect on footstep impact localization, especially in the case of multiple occupants walking on the same instrumented area. Therefore, in this paper, a footstep detection algorithm is proposed and analyzed. The performance of the proposed algorithm is evaluated using occupant walking experiments on an instrumented floor section, inside an operational smart building. Additionally, the detected footsteps are localized using an energy-based localization method. Footstep detection and localization performances are compared between single occupant and multiple occupant cases.

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