Classifying Subway Passengers Based on Mobile Network Data Analysis

Mobile users can be profiled through network data analysis. The classification of subway passengers will help improve operating efficiency and safety. Here, we investigate how to classify mobile service users using subway networks. We not only discuss mobile subway user data analytics in general but also present the entire process of wireless data collection and big data analytics. We first introduce the characteristics of external data recording (XDR) collected from deep packet inspection (DPI) device in current wireless networks. We then propose an algorithm to distinguish subway residents from commuters. Finally, we examine the use and performance of several machine learning algorithms to classify spatio-temporal and service usage patterns of mobile users. Through the accurate classification of users, operators can provide personalized service.