Prediction of Moving Object Location Based on Frequent Trajectories

Recent advances in wireless sensors and position technology provide us with unprecedent amount of moving object data. The volume of geospatial data gathered from moving objects defies human ability to analyze the stream of input data. Therefore, new methods for mining and digesting of moving object data are urgently needed. One of the popular services available for moving objects is the prediction of the unknown location of an object. In this paper we present a new method for predicting the location of a moving object. Our method uses the past trajectory of the object and combines it with movement rules discovered in the moving objects database. Our original contribution includes the formulation of the location prediction model, the design of an efficient algorithm for mining movement rules, the proposition of four strategies for movement rule matching with respect to a given object trajectory, and the experimental evaluation of the proposed model.