GeoHash tag based mobility detection and prediction for traffic management

Abstract

User mobility detection and prediction can help in many ways for planning and monitoring a population distribution and displacement in a specific area or location. It also helps in planning for resource distribution and allocation. In this paper, we present a study on the mobility of the population which can be monitored by sensors, GPS devices through location detection. All the public transports like buses, taxis, etc. have GPS devices posted that can provide movement of a vehicle in city traffic. For experimental analysis, the T-Drive Taxi Trajectories dataset was selected, in which taxi location data are collected with the information of taxi ID, timestamp, latitude, and longitude. GeoHash tags were generated for the location of a taxi based on latitude and longitude. A graph was built based on vertices as GeoHash tag and edges as a direct link between the GeoHash tags. Graph-Based data analysis was applied to identify the importance of GeoHash tag based on the in-degree and PageRank of the vertices. The mobility path and movement of traffic can be predicted that can be used for disaster management and urban development for city planning.