Latitude, longitude, and beyond: mining mobile objects' behavior

Mitra Baratchi

    Research output: ThesisPhD Thesis - Research UT, graduation UT

    257 Downloads (Pure)

    Abstract

    Rapid advancements in Micro-Electro-Mechanical Systems (MEMS), and wireless communications, have resulted in a surge in data generation. Mobility data is one of the various forms of data, which are ubiquitously collected by different location sensing devices. Extensive knowledge about the behavior of humans and wildlife is buried in raw mobility data. This knowledge can be used for realizing numerous viable applications ranging from wildlife movement analysis, to various location-based recommendation systems, urban planning, and disaster relief. With respect to what mentioned above, in this thesis, we mainly focus on providing data analytics for understanding the behavior and interaction of mobile entities (humans and animals). To this end, the main research question to be addressed is: How can behaviors and interactions of mobile entities be determined from mobility data acquired by (mobile) wireless sensor nodes in an accurate and efficient manner? To answer the above-mentioned question, both application requirements and technological constraints are considered in this thesis. On the one hand, applications requirements call for accurate data analytics to uncover hidden information about individual behavior and social interaction of mobile entities, and to deal with the uncertainties in mobility data. Technological constraints, on the other hand, require these data analytics to be efficient in terms of their energy consumption and to have low memory footprint, and processing complexity.
    Original languageEnglish
    Awarding Institution
    • University of Twente
    Supervisors/Advisors
    • Havinga, Paul J.M., Supervisor
    • Skidmore, Andrew , Supervisor
    • Meratnia, Nirvana , Advisor
    Thesis sponsors
    Award date24 Jun 2015
    Place of PublicationEnschede
    Publisher
    Print ISBNs978-90-365-3892-3
    DOIs
    Publication statusPublished - 24 Jun 2015

    Keywords

    • mobility data analysis
    • Big data
    • DB-DM: DATA MINING
    • Data Mining
    • EWI-26149
    • Ubiquitous Computing

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