Detecting Representative Trajectories in Moving Objects Databases from Clusters

Abstract

The analysis of the information of moving objects is increasingly important and useful, thanks to the new technology that allows the acquisition, storage, and representation of movement over time. We can resort to techniques that allow discovering implicit information in the movement of objects through computational techniques, one of them is the discovery of trajectory patterns and a representative trajectory to summarize cluster in one path, and also the identification of anomalies, both allow to describe the movement of the trajectory. The representative trajectories found in this work, it could be useful to understand movement in moving objects like cars, airplanes, buses. In this work, we show results with real data of massive mobility transport like Transmilenio in Bogotá – Colombia, wherefrom raw data we can found a movement pattern using Spatio-temporal databases, these patterns found represent movement tendency of moving objects that can facilitate representation, visualization and decision making in transport systems.