Design Of Monitoring System Of Campus Students' Adjoint Behavior Based On Spatiotemporal Data Analysis

With the rapid development of mobile communication,smart phones have become a necessity of entertainment communication.With the increasing maturity of Wi Fi technology and the continuous reduction of equipment cost,the popularity of Wi Fi network is gradually increasing,and users' dependence on Wi Fi network is gradually increasing when they use mobile phones to access the Internet in fixed places.When the smartphone turns on the Wi Fi function,it will automatically send Wi Fi packets to the surrounding environment,including the information of the phone holder.Wi Fi data naturally contains time and space information,so collecting mobile wifi data and analyzing and mining it can reveal smartphone user behavior patterns,mobile laws and social relations.In this paper,we propose a monitoring system of students' accompanying behavior in campus.The modules of the system include the collection and preprocessing of students' spatiotemporal trajectory data,the design of the algorithm of accompanying behavior mining and the construction of social network graph.In this paper,Wi Fi probe is used to collect the information of students' spatiotemporal trajectory,and different algorithms for mining adjoint behavior are proposed from two different scales,including multiple buildings and only one building.In this paper,STS-AB(Semantic Trajectory Similarity for Adjoint Behavior)algorithm is proposed for the large-scale situation of multiple buildings in the whole campus,that is,the adjoint behavior mining algorithm based on semantic trajectory similarity;in the small-scale situation of a specific building site,RTS-AB(RSSI Trend Similarity for Adjoint Behavior)algorithm is proposed Behavior)algorithm,which is based on the trend similarity of RSSI.According to the results of adjoint behavior mining algorithm,students' social network graph can be constructed.This experiment collects the Wi Fi data of middle school students in the East Campus of Huazhong University of science and technology,and uses the accompanying behavior monitoring system proposed in this paper to mine the accompanying behavior of students.Using the Wi Fi data of volunteers to verify the system proposed in this paper,it is concluded that the STS-AB algorithm and RTS-AB algorithm proposed in this paper arefeasible,and the accompanying behavior monitoring system can accurately measure the accompanying behavior and intimate relationship between students.