Abstract
Room-level occupancy estimation is a critical input for real estate management, including building utilization optimization, energy-efficient building control, building security, and occupant health and well-being. Knowing how many people are using a room at a time can enable businesses to use their real estate, energy and human capital more efficiently, reducing operating expenses as well as carbon footprint. Radar-based occupancy estimation is attractive because it is unobtrusive and does not introduce the privacy issues brought with video imaging-based sensors. In this paper, we present an occupant estimation approach based on continuous wave Doppler radar and wavelet-based signal processing techniques. Theoretical background provides a rational for using a wavelet-based time-frequency approach, and comprehensive simulation and experimental results demonstrate the effectiveness of the proposed approaches on a data set that includes 1–10 occupants. These results indicate that Doppler radar with wavelet-based signal processing may be an effective tool for occupant count in smart building applications.
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