Abstract
Zone-level occupancy counting is a critical technology for smart buildings and can be used for applications, such as building energy management, surveillance, and public safety. Existing occupancy counting techniques typically require installation of large number of occupancy monitoring sensors inside a building and an established wireless network. In this paper, in order to achieve occupancy counting, we consider the use of Wi-Fi probe requests that are continuously transmitted from Wi-Fi enabled smart devices for discovering nearby access points. To this end, Wi-Fi Pineapple equipment are used for passively capturing ambient probe requests from Wi-Fi devices, such as smart phones and tablets, where no connectivity to a Wi-Fi network is required. This information is then used to localize users within coarsely defined occupancy zones, and subsequently to obtain occupancy count within each zone at different time scales. An interacting multimodel (IMM) Kalman filter technique is developed to improve occupancy counting accuracy. Our numerical results using Wi-Fi data collected at a university building show that the use of Wi-Fi probe requests in conjunction with IMM-based Kalman filters can be a viable solution for zone-level occupancy monitoring in smart buildings.