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Detecting movement patterns with wireless sensor networks: application to bird behavior

Abstract : More and more animal species are endangered every day on earth. In order to study their adaptation to world and climate change and their chances of survival, numerous initiatives have been taken that mostly need human intrusion into animal communities. Today mobile devices enable researchers to go beyond this limit. In this paper, we propose an original solution that consists on a new framework for detecting individual songs in a bird population and identifying remotely by this way their collective behavior in movements without human interaction. Movement patterns are elicited by analyzing data collected via wireless sensors fitted with microphone. Whereas similar methods use mobile devices fitted on some specimens, we rather propose fixed sensors. We demonstrate that this solution provides a good answer to technical constraints assessed by the context and we discuss results of experimental simulations that allow to define optimized parameters for the architecture to be set up on the ground. Experimental results are provided and show the relative impact of different parameters such as the number of sensors or the population size on the detection rate.
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Conference papers
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Contributor : Martine Collard <>
Submitted on : Monday, June 20, 2011 - 3:56:29 AM
Last modification on : Wednesday, July 18, 2018 - 8:11:27 PM


  • HAL Id : hal-00601641, version 1



Erick Stattner, Martine Collard, Philippe Hunel, Nicolas Vidot. Detecting movement patterns with wireless sensor networks: application to bird behavior. 8th International Conference on Advances in Mobile Computing and Multimedia (MOMM 2010), Nov 2010, France. pp.251-258. ⟨hal-00601641⟩



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