Occupant Activity Level Estimation Using Floor Vibration.

Occupant activity level information is essential in many smart home applications, such as energy management and elderly care. Various methods have been proposed for detecting occupant activities through vision-, acoustic-, or radio frequency-based methods. However, the visual-based methods function only when occupants are in the visual field, the acoustic-based methods are sensitive to noise, and the radio-based methods usually require occupants to carry receivers all the time. These requirements increase the difficulty of deployment and maintenance in typical indoor smart home scenarios. To overcome these shortcomings, we propose a structural vibration-based approach. Specifically, we develop a system with sparse sensor configuration deployed in the floor to monitor the activity levels of different areas. Compared to vision- and acoustic-based methods, our method is not restricted by line-of-sight and less influenced by noise. Compared to the access control system (ground truth), our system enables finer grained activity level estimation with a comparable resolution. We evaluate our system in a real-world deployment in an office building and used the building access control as the ground truth system. Our system shows a correlation coefficient at 0.836 when compared to the ground truth systems.