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An adaptive energy management scheme for real-time landslide detection

Published: 11 November 2013 Publication History

Abstract

Sensor nodes in wireless sensor network are powered by batteries and thus the utilization of effective energy management techniques becomes one of the most important challenges in realistic design of WSN. This paper deals with an optimal energy management scheme in Landslide detection system deployed in Kerala. Based on the meteorological, hydrological and soil parameters, sensors will be dynamically prioritized, scheduled and selects appropriate sensors for event handling. The results of this research work shows that the life time of the network has been improved due to the implementation of this adaptive energy management scheme.

References

[1]
Ramesh, M. V. Design, Development, and Deployment of a Wireless Sensor Network for Detection of Landslides. Ad Hoc Networks, Elsevier, 2012
[2]
Sheth, A. and C. A., "Senslide: A distributed landslide prediction system.
[3]
Deokwoo Jung, T. T. and Savvides, A. Sensor node lifetime analysis: Models and tools. ACM Transactions on Sensor Networks, March 2007.
[4]
Yunbo Wang, M. C. V. and Goddard, S. Stochastic analysis of energy consumption in wireless sensor network. IEEE Communications Society Conference on Sensor Mesh and Ad Hoc Communications and Networks (SECON), 2010

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  1. An adaptive energy management scheme for real-time landslide detection

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      cover image ACM Conferences
      SenSys '13: Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems
      November 2013
      443 pages
      ISBN:9781450320276
      DOI:10.1145/2517351
      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Publication History

      Published: 11 November 2013

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      Author Tags

      1. distributed algorithms
      2. energy optimization
      3. wireless sensor network

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      SenSys '13 Paper Acceptance Rate 21 of 123 submissions, 17%;
      Overall Acceptance Rate 198 of 990 submissions, 20%

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