Enhancing the quality of geometries of interest (GOIs) extracted from GPS trajectory data using spatio-temporal data aggregation and outlier detection

Abstract

One of the initial phases in the applications dealing with data processing on GPS trajectory data is to generate the time-stamped Sequence of Visited Locations (SVLs) of the mobile objects. The sequence is constructed by labeling each of the GPS observations of the trajectory using the ID of their intersecting Geometries of Interest (GOIs). In this paper, we enhance the performance of the state-of-the-art scheme for constructing the GOIs of a mobile object by proposing a data aggregation and outlier detection method. Our experimental results using geometric similarity metrics show that our improved GOI construction method outperforms the baseline methods by constructing the GOIs remarkably m..