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Journal of Sensors
Volume 2016, Article ID 9350928, 28 pages
http://dx.doi.org/10.1155/2016/9350928
Research Article

On Event/Time Triggered and Distributed Analysis of a WSN System for Event Detection, Using Fuzzy Logic

Department of Electrical and Computer Engineering, University of Patras, Eratosthenous 6, Rio, 26500 Patras, Greece

Received 14 December 2015; Accepted 15 March 2016

Academic Editor: Matthew J. Whelan

Copyright © 2016 Sofia Maria Dima et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Event detection in realistic WSN environments is a critical research domain, while the environmental monitoring comprises one of its most pronounced applications. Although efforts related to the environmental applications have been presented in the current literature, there is a significant lack of investigation on the performance of such systems, when applied in wireless environments. Aiming at addressing this shortage, in this paper an advanced multimodal approach is followed based on fuzzy logic. The proposed fuzzy inference system (FIS) is implemented on TelosB motes and evaluates the probability of fire detection while aiming towards power conservation. Additionally to a straightforward centralized approach, a distributed implementation of the above FIS is also proposed, aiming towards network congestion reduction while optimally distributing the energy consumption among network nodes so as to maximize network lifetime. Moreover this work proposes an event based execution of the aforementioned FIS aiming to further reduce the computational as well as the communication cost, compared to a periodical time triggered FIS execution. As a final contribution, performance metrics acquired from all the proposed FIS implementation techniques are thoroughly compared and analyzed with respect to critical network conditions aiming to offer realistic evaluation and thus objective conclusions’ extraction.