Research On User Mobility Based On Campus WiFi Detection

With the arrival of the mobile Internet era and the popularity of campus wireless local area network,in order to meet the needs that students and teachers can access wireless network anytime,more and more campus are covered with wireless network.It makes obtain the user's location information through the monitoring of wireless signal possible,which provides a large amount of data for the study of mobile campus users.Therefore,in order to betterly understand the learning pattern and the behavior characteristic of the students,this paper mainly based on the data collected by the WiFi probe in the campus to carry on the user's mobility research.The main work of this paper is as follows:1)Firstly,this paper makes a deep research on the mobility of human beings,and expounds the research progress of spatial and temporal characteristics of human movement.Then it analyzes the merits and drawbacks and the application scenarios of different trajectory data acquisition methods.And the application of data mining technology in trajectory data is studied.At last,the research status and existing problems of mobile location prediction are described in detail.2)Design and implement a mobility analysis system which includes data acquisition,data preprocessing,data visualization analysis and display.The work flow of this system is as follows:Firstly,the wireless request signal of the users' intelligent terminal is acquired by deploying the WiFi probes in the campus;Then,we filter the fixed and weak signal strength equipment and the devices which cannot find the corresponding equipment manufacturers.Finally,the results are presented in the form of Web by using data visualization technology.3)Based on the mobility analysis system,the paper analyzes and displays the real-time traffic flow,the result of mining moving object's trajectory pattern,the users' mobility law.In the last,the analysis results will be explained.4)A location prediction algorithm based on probabilistic suffix tree is proposed.The prediction algorithm considers not only the spatial historical trajectories but also the corresponding probabilities about the time when objects appear.The paper firstly analyzes the principle of the position prediction theoretically.Then it focuses on how to create predict the algorithm model and predict next location.In the end,the paper has carried on the experiment to the proposed location prediction algorithm and the prediction algorithm based on Markov model,and the experimental results are analyzed.