Abstract
Continuously tracking mobility of humans, vehicles or merchandise not only provides streaming, real-time information about their current whereabouts, but can also progressively assemble historical traces, i.e., their evolving trajectories. In this paper, we outline a framework for online detection of groups of moving objects with approximately similar routes over the recent past. Further, we propose an encoding scheme for synthesizing an indicative trajectory that collectively represents movement features pertaining to objects in the same group. Preliminary experimentation with this multiplexing scheme shows encouraging results in terms of both maintenance cost and compression accuracy.
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Patroumpas, K., Toumbas, K., Sellis, T. (2012). Multiplexing Trajectories of Moving Objects. In: Ailamaki, A., Bowers, S. (eds) Scientific and Statistical Database Management. SSDBM 2012. Lecture Notes in Computer Science, vol 7338. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31235-9_42
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DOI: https://doi.org/10.1007/978-3-642-31235-9_42
Publisher Name: Springer, Berlin, Heidelberg
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