Application of Human Mobility Data to Support Regional Policy Decision-Making for an Inclusive Society

Abstract

We define the residential areas of new and old residents based on the age of the properties, and visualize and model the spatial interaction between new and old residents in the town during the daytime using location data collected through a smartphone application. By measuring the daytime human mobility flow and diversity of the population in each area using entropy, we can visualize the spatial segmentation between old and new residents. We propose a human mobility model based on the statistics of the outing rate, the time spent in each place, and the network of human flows connecting the origin and destination places of the movement. We also propose a recommendation system for places and facilities, which gently improves the segregation in the human flow network. These will provide scientific support for local policies in creating communities where new and old residents cooperate with each other.