Research And Implementation Of Trajectory Data In Participatory Sensing System

With the rapid development of mobile terminals,the sensors of the smartphones have been widely used.At the same time,the concept of participatory sensing is wide-coverage,in which users are both the beneficiaries and contributors of the data.Among these data,users' trajectory data is convenient and worthy to be collected.Besides,location-based applications have become highly popular over the world.Increasing number of people is using GPS-enabled devices to log their locations and share information with others.Under this situation,it seems that analyzing users'trajectories becomes very important.It has been proven beneficial in many different ways,including for mobility patterns analyzing,personalized recommendation,social tie detection and so on.Thanks to the rich information contained in trajectory data,this dissertation mainly introduces the researches and implementations based on trajectory data in participatory sensing system.In participatory sensing environment,trajectory prediction is helpful to predict users' movement tendency and encourage them to upload data to the platform.Besides,privacy problem is a hot topic in participatory sensing system,and there exists close relationship between trajectory analyzing and social tie discovering,so in this dissertation we also propose an approach to infer social ties via analyzing users' trajectory with privacy protection.Firstly,the theory and technical background of participatory sensing and trajectory analyzing are introduced in this dissertation.Secondly,the main research points of this dissertation are introduced.Then,we describe the design and implementation procedure of trajectory analyzing module and platform management system in participatory sensing platform.Finally,we use the real data set to evaluate our approach and test functions in our system.