Title: Use of wireless sensor networks for distributed event detection in disaster management applications

Authors: Majid Bahrepour; Nirvana Meratnia; Mannes Poel; Zahra Taghikhaki; Paul J.M. Havinga

Addresses: University of Twente, 7500 AE, Enschede, The Netherlands. ' University of Twente, 7500 AE, Enschede, The Netherlands. ' University of Twente, 7500 AE, Enschede, The Netherlands. ' University of Twente, 7500 AE, Enschede, The Netherlands. ' University of Twente, 7500 AE, Enschede, The Netherlands

Abstract: Recently, wireless sensor networks (WSNs) have become mature enough to go beyond being simple fine-grained continuous monitoring platforms and have become one of the enabling technologies for early-warning disaster systems. Event detection functionality of WSNs can be of great help and importance for (near) real-time detection of, for example, meteorological natural hazards and wild and residential fires. From the data-mining perspective, many real world events exhibit specific patterns, which can be detected by applying machine learning (ML) techniques. In this paper, we introduce ML techniques for distributed event detection in WSNs and evaluate their performance and applicability for early detection of disasters, specifically residential fires. To this end, we present a distributed event detection approach incorporating a novel reputation-based voting and the decision tree and evaluate its performance in terms of detection accuracy and time complexity.

Keywords: disaster early warning systems; distributed event detection; wireless sensor networks; WSNs; situated computing; disaster management; emergency management; natural hazards; wild fires; residential fires; data mining; machine learning; reputation based voting; decision trees.

DOI: 10.1504/IJSSC.2012.045569

International Journal of Space-Based and Situated Computing, 2012 Vol.2 No.1, pp.58 - 69

Received: 16 Jul 2011
Accepted: 21 Nov 2011
Published online: 20 Sep 2014 *

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