Generating Heat Maps of Popular Routes Online from Massive Mobile Sports Tracking Application Data in Milliseconds While Respecting Privacy

Abstract

The breakthrough of GPS-equipped smartphones has enabled the collection of track data from human mobility on massive scales that can be used in route recommendation, urban planning and traffic management. In this work we present a fast map server that can generate and visualize heat maps of popular routes online from massive sports track data based on client preferences, e.g., running routes lasting less than an hour. The heat maps shown respect user privacy by not showing routes with less than a predefined number of different users, for instance five. The results are represented to the client using a dynamic tile layer. The current implementation uses data collected by the Sports Tracker mobile application with over 800,000 different tracks and 2.8 billion GPS data points. Stress tests indicate that the server can handle hundreds of simultaneous client requests in a single server configuration.

Keywords

• big data
• heat map
• data privacy