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Sri Vasavi College, Erode Self-Finance Wing, 3rd February 2017. National Conference on Computer and Communication, NCCC’17. International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)

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Wireless Sensor network is having tremendous growth in current world due to low cost sensor and well planned techniques. Wireless sensor networks (WSNs) have become mature enough to go beyond being simple fine-grained continuous monitoring platforms and become one of the enabling technologies for disaster early-warning systems. This technology can be used to detect the particular event which can be helpful to manage the disaster. Until now various techniques of event detection have come forward and effectively contributed to manage the disaster. In this paper, we introduce ML (Machine Learning) 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 to evaluate its performance in terms of detection accuracy and time complexity.


[1]M. Sheik Dawood, G. Athisha,“FaultTolrent Sensor Network Protocol for Disaster Management”, Journal of Global Research in Computer Science, Vol. 4, No. 6, June 2013, PP.1-10.

[2] A. Arora, “ExScal: Elements of an Extreme Scale WirelessSensor Network”, Proc. 11th IEEE International Conference on Embedded Real-Time Computing System Applications, Aug. 2005, pp. 102–108.

[3] T. He, “VigilNet: An Integrated Sensor Network System for Energy-Efficient Surveillance”, ACM Transaction Sensor Network, vol. 2, no. 1, 2006, pp. 1–38.

[4] A. Wood, “Context-Aware Wireless Sensor Networks for Assisted Living and Residential Monitoring”, IEEE Network, vol. 22, no. 4, July 2008, pp. 26–33.

[5] Harminder Kaur, Ravinder Singh Sawhney, Navita Komal, “Wireless Sensor Networks for Disaster Management”,International Journal of Advanced Research in Computer Engineering & Technology Volume 1, Issue 5, July 2012.

[6] Rehna Raj, Maneesha Ramesh, V. And Sangeeth Kumar, “Fault Tolerant Clustering Approaches in WSN for Landslide Area Monitoring”,Proceedings of the International Conference on Wireless Networks (ICWN„08), Vol. 1, 2008, pp. 107–113.

[7] KalyanaTejaswi, Prakshep Mehta, Rajat Bansal, Chandresh Parekh,S. N. Merchant and U. B. Desai, “Routing Protocols for Landslide Prediction using Wireless Sensor Networks”, proceedings of fourth International Conference on Intelligent Sensing and Information Processing (ICISIP 2006),2006,pp.43-47.

[8] Alberto Rosi, Nicola Bicocchi, Gabriella Castelli, Marco Mamei, Franco Zambonelli, “Landslide Monitoring with Sensor network”, International journal of signal and imaging systems engineering, Vol. 10, no. 3, 2011.

[9]. SitiKhairunnizaBejo, Abdul Rashid Mohamed Shariff, “Historical Analysis of the Land Movement in Landslide Area Using Elastic Image Registration and Conditional Statement approach”, International Journal of Multimedia and Ubiquitous Engineering, Vol. 6, no. 3, 2011.

[10] M. Sheik Dawood, SajinSalim, S. Sadasivam, G. Athisha, “Energy Efficient Modulation Techniques for Fault Tolerant Two-Tiered Wireless Sensor Networks”, Journal of Asian scientific


Disaster Early Warning Systems, Event Detection, Sensor Networks

  • Format Volume 5, Issue 1, No 13, 2017
  • Copyright All Rights Reserved ©2017
  • Year of Publication 2017
  • Author S.Dhivya, Mrs.Dr.P.Sumitra,
  • Reference IJCS-216
  • Page No 1348-1353

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