Indoor occupancy estimation using the LTE-CommSense system

Indoor occupancy estimation is necessary for the efficient operation of smart buildings. The development of an efficient algorithm to estimate indoor occupancy will allow better control and optimization of the heating, ventilation, and air conditioning (HVAC) methods of the whole building. Various methods are proposed in the open literature, which depends on environmental sensor data, image or video data, smartphone data, and radio frequency (RF) signals. This work proposes a unique non-intrusive, low cost, passive indoor occupancy estimation solution using our novel instrumentation scheme. We call it Long-Term Evolution (LTE) communication infrastructure-based environment sensing or LTE-CommSense. It requires no signal transmission and uses LTE communication radiation using passive radar principle. Therefore, the system is less complex, has a low footprint and consumes low power requiring no regulations related to radar signal transmissions. This system uses practical data to first determine whether the indoor environment is empty or not. If not, it estimates the number of people occupying the room. Performance evaluation with practical data confirms the feasibility of this proposed approach. Consistency of this approach is verified by using data captured at different dates and times with a different set of people.