Geo-Visualization of Spatial Occupancy on Smart Campus Using Wi-Fi Connection Log Data

As a typical and special type of urban setting, the university campus usually faces similar challenges as cities raised by high-density inhabitants. The smart campus has been introduced based on the smart city, as concepts, technologies, and solutions to improve livability and energy efficiency. Inhabitants' occupancy in buildings and open spaces on campus is critical to optimize campus management and services. Information about spatial occupancy of campus inhabitants can be produced based on various location-based solutions, such as global navigation satellite systems (GNSS), campus cameras, Bluetooth, and Wi-Fi. As an essential component in campus information infrastructure, Wi-Fi network covers almost the entire university campus and has advantages in collecting locations of campus inhabitants. In this paper, geo-visualization of spatial occupancy of campus inhabitants is designed and implemented using anonymized Wi-Fi network log data. First, 3-dimension building models are reconstructed based on LiDAR point clouds and construction drawings. Then, the Wi-Fi network log data are cleaned and preprocessed. Campus inhabitants' locations are extracted from structural Wi-Fi data. Geo-visualization at room, floor, and building levels is designed and implemented. On a temporal dimension, spatial occupancy can be visualized by each second, minute, hour, or day of the week in 3D buildings. The implementation of the geo-visualization is based on CesiumJS, which offers an interface for 3D-animated visualization and interaction. The research can be used to support university management and educators to implement the smart campus and optimize pedagogical research.