Privacy Preserving Occupancy Detection Using NB IoT Sensors

Occupancy detection is crucial when trying to lower the emissions that a building produces. Some buildings are equipped with motion sensors or cameras to find how many occupants are in a room. However, this is not entirely accurate as people could be stationary in situations like sitting at a desk or watching television. Using environmental sensors, we can determine if a room is occupied even if the occupants are not moving. When occupants are inside a room, they give off extra CO2 or increase the room's temperature. We can find the small differences in the environmental values used to accurately predict a room's occupancy levels. We use relatively inexpensive IoT sensors that almost every building's HVAC system should have in the near future. We apply K-means clustering with success to predict occupancy levels. Our algorithms can be used in smart thermostats to automatically adjust the room's heat depending on how many occupants are in a room.