Analysis and Modeling of Mobile Phone Activity Data Using Interactive Cyber-Physical Social System

Mobile networks possess significant information and thus are considered a gold mine for the researcher's community. The call detail records (CDR) of a mobile network are used to identify the network's efficacy and the mobile user's behavior. It is evident from the recent literature that cyber-physical systems (CPS) were used in the analytics and modeling of telecom data. In addition, CPS is used to provide valuable services in smart cities. In general, a typical telecom company has millions of subscribers and thus generates massive amounts of data. From this aspect, data storage, analysis, and processing are the key concerns. To solve these issues, herein we propose a multilevel cyber-physical social system (CPSS) for the analysis and modeling of large internet data. Our proposed multilevel system has three levels and each level has a specific functionality. Initially, raw Call Detail Data (CDR) was collected at the first level. Herein, the data preprocessing, cleaning, and error removal operations were performed. In the second level, data processing, cleaning, reduction, integration, processing, and storage were performed. Herein, suggested internet activity record measures were applied. Our proposed system initially constructs a graph and then performs network analysis. Thus proposed CPSS system accurately identifies different areas of internet peak usage in a city (Milan city). Our research is helpful for the network operators to plan effective network configuration, management, and optimization of resources.