Mohammad Etmad was a PhD student at Faculty of Computer Science of Dalhousie University. His research focused on trajectory data mining. His supervisors were Prof. Stan Matwin and Prof. Luís Torgo.

PhD Thesis

Title: Segmentation Algorithms for Trajectory Data

Summary:

An enormous number of mobility datasets for tracking animals, vehicles, vessels, individuals and moving objects are currently available, and this number continues to grow. Mobility data has a diversity of applications including transportation, marine navigation, tourism, animal behavior analysis, environmental science. Since the rate of generation of the mobility data is exceptionally high, processing such data demands some reasonable preprocessing and cleaning steps. Segmenting the traces of movements in mobility data is an essential task for preprocessing, which is called trajectory segmentation. The significance of this preprocessing step has three dimensions. First, it is crucial to data sammarization, so that it can alleviate the curse of dimensionality. Second, correctly using a segmentation method can contribute to increase the level of preserving the privacy of mobility data. Third, it can be employed in embedded systems to diminish energy consumption and make mobility sensor devices operating for a longer time.

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You may get more information at Mohammad’s Home Page