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Characterization of Field-of-View for Energy Efficient Application-Aware Visual Sensor Networks

AMJAD, Anas, PATWARY, Mohammad, GRIFFITHS, Alison and SOLIMAN, Abdel-Hamid (2016) Characterization of Field-of-View for Energy Efficient Application-Aware Visual Sensor Networks. IEEE Sensors Journal, 16 (9). pp. 3109-3122. ISSN 1530-437X

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Official URL: http://dx.doi.org/10.1109/JSEN.2016.2523266

Abstract or description

Energy consumption is one of the primary concerns in a resource constrained Visual Sensor Network. The existing Visual Sensor Network design solutions under particular resource constrained scenarios are application specific; whereas the degree of sensitivity of any of these resource constrains (e.g. energy etc) varies from one application to another. This limits the implementation of the existing energy efficient solutions within a Visual Sensor Network node which may be considered to be a part of a heterogeneous network. The heterogeneity of image capture and processing within a Visual Sensor Network can be adaptively reflected with a dynamic Field-of-View realisation. This is expected to allow the implementation of a generalised energy efficient solution to adapt with the heterogeneity of the network. In this paper, an energy efficient Field-of-View characterisation framework is proposed which can support a diverse range of applications. The context of adaptivity in the proposed Field-of-View characterisation framework is considered to be: a) sensing range selection; b) maximising spatial coverage; c) adaptive task classification and d) minimising the number of required nodes. Soft decision criteria is exploited and it is observed that for a given detection reliability, the proposed framework provides energy efficient solutions which can be implemented within heterogeneous networks. It is also found that the proposed design solution for heterogeneous networks leads to 49.8% energy savings compared to the trivial design solution.

Item Type: Article
Faculty: Previous Faculty of Computing, Engineering and Sciences > Engineering
Depositing User: Alison GRIFFITHS
Date Deposited: 30 Sep 2016 10:41
Last Modified: 24 Feb 2023 13:43
URI: https://eprints.staffs.ac.uk/id/eprint/2420

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