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Qualitative change detection using sensor networks based on connectivity information

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Abstract

The research reported in this paper uses wireless sensor networks to provide salient information about spatially distributed dynamic fields, such as regional variations in temperature or concentration of a toxic gas. The focus is on deriving qualitative descriptions of salient changes to areas of high-activity that occur during the temporal evolution of the field. The changes reported include region merging or splitting, and hole formation or elimination. Such changes are formally characterized, and a distributed qualitative change reporting (QCR) approach is developed that detects the qualitative changes simply based on the connectivity between the sensor nodes without location information. The efficiency of the QCR approach is investigated using simulation experiments. The results show that the communication cost of the QCR approach in monitoring large-scale phenomena is an order of magnitude lower than that using the standard boundary-based data collection approach, where each node is assumed to have its location information.

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Acknowledgements

This material is based upon work supported by the National Science Foundation under Grant numbers IIS-0429644 and IIS-0534429. Mike Worboys’ work is also supported by the National Science Foundation under NSF grant numbers DGE-0504494 and BCS-0327615.

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Authors and Affiliations

  1. Department of Spatial Information Science and Engineering, University of Maine, Orono, ME, 04468, USA

    Jixiang Jiang, Michael Worboys & Silvia Nittel

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  1. Jixiang Jiang
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  2. Michael Worboys
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  3. Silvia Nittel
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Correspondence to Jixiang Jiang.

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Jiang, J., Worboys, M. & Nittel, S. Qualitative change detection using sensor networks based on connectivity information. Geoinformatica 15, 305–328 (2011). https://doi.org/10.1007/s10707-009-0097-0

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  • DOI: https://doi.org/10.1007/s10707-009-0097-0

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