Location-centric flow flux for improved indoor mobility models

Understanding the mobile user flow flux patterns is important for numerous applications relevant to crowd movement, from information sharing, networking, to security and public health. Particularly in instances of smart buildings and hospitals, among others, the flow between indoor locations, and mobility modeling within buildings is of a prime significance. Much of the mobility modeling studies have focused on a user-centric approach for outdoors movement. In this study, we take a location-centric approach for indoor mobility to analyze and characterize region relationships as pertains to user flow. Our study is trace-driven, as we use extensive measurements from wireless LANs, and mine them to quantify metrics for influx and outflux and show their stability for various buildings at university campus involving more than 108K anonymous mobile users and more than 3 million records. The flux degrees are shown to be temporally stable where their coefficient of variations do not exceed 0.42. However, the correlation between the degrees and dynamic spatial density is not always strongly positive and it varies between buildings. Finally, we outline several smart buildings applications of location-centric flow flux.