Decentralized Movement Pattern Detection amongst Mobile Geosensor Nodes

  • Authors:
  • Patrick Laube;Matt Duckham;Thomas Wolle

  • Affiliations:
  • Department of Geomatics, The University of Melbourne, Australia VIC 3010;Department of Geomatics, The University of Melbourne, Australia VIC 3010;NICTA Sydney, Alexandria, Australia NSW 1435

  • Venue:
  • GIScience '08 Proceedings of the 5th international conference on Geographic Information Science
  • Year:
  • 2008

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Abstract

Movement patterns, like flockingand converging, leadingand following, are examples of high-level process knowledge derived from low-level trajectory data. Conventional techniques for the detection of movement patterns rely on centralized "omniscient" computing systems that have global access to the trajectories of mobile entities. However, in decentralized spatial information processing systems, exemplified by wireless sensor networks, individual processing units may only have access to localinformation about other individuals in their immediate spatial vicinity. Where the individuals in such decentralized systems are mobile, there is a need to be able to detect movement patterns using collaboration between individuals, each of which possess only partial knowledge of the global system state. This paper presents an algorithm for decentralized detection of the movement pattern flock, with applications to mobile wireless sensor networks. The algorithm's reliability is evaluated through testing on simulated trajectories emerging from unconstrained random movement and correlated random walk.