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Decentralized Movement Pattern Detection amongst Mobile Geosensor Nodes

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Book cover Geographic Information Science (GIScience 2008)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5266))

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Abstract

Movement patterns, like flocking and converging, leading and 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 local information 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.

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Author information

Authors and Affiliations

  1. Department of Geomatics, The University of Melbourne, VIC 3010, Australia

    Patrick Laube & Matt Duckham

  2. NICTA Sydney, Locked Bag 9013, Alexandria, NSW 1435, Australia

    Thomas Wolle

Authors
  1. Patrick Laube
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  2. Matt Duckham
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  3. Thomas Wolle
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Editor information

Thomas J. Cova Harvey J. Miller Kate Beard Andrew U. Frank Michael F. Goodchild

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© 2008 Springer-Verlag Berlin Heidelberg

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Laube, P., Duckham, M., Wolle, T. (2008). Decentralized Movement Pattern Detection amongst Mobile Geosensor Nodes. In: Cova, T.J., Miller, H.J., Beard, K., Frank, A.U., Goodchild, M.F. (eds) Geographic Information Science. GIScience 2008. Lecture Notes in Computer Science, vol 5266. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87473-7_13

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  • DOI: https://doi.org/10.1007/978-3-540-87473-7_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-87472-0

  • Online ISBN: 978-3-540-87473-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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