Cloudtp: A cloud-based flexible trajectory preprocessing Framework

Trajectory data preprocessing is to convert raw GPS logs into organized trajectories, which is a common, necessary but tedious task in many urban applications. This paper proposes CloudTP, a cloud-based flexible trajectory data preprocessing framework, to provide an efficient online service, easing the burdens of urban application builders. The proposed system is designed and implemented based on the cloud storage and parallel computing framework (i.e. Spark). Its features consist of 1) noise filtering, 2) trajectory segmentation, 3) map matching, and 4) index building. CloudTP is useful for both normal users and advanced users. By simply uploading trajectory datasets and setting corresponding parameters, normal users can get organized trajectories, statistics and visualizations on the cloud, while advanced users can also customize their own algorithms in any preprocessing module. Finally, usage scenarios are demonstrated to show the capability and flexibility of CloudTP.