Preventing Forest Animals from Train Accidents Using Outlier-Analysis Algorithm in WSN

  • V. P. Jayachitra
  • Sumalatha Ramachandran
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 132)


In the recent decade the incidence of animal fatalities involving trains has remained high in the country. According to recent survey by Wildlife Trust of India (WTI), 72 animals are dying each year due to collision with speeding trains. Its high time we protect the lives of endangered species of animals. Though railway authorities ordered the drivers to reduce the speed of the trains inside forest areas, it does not have any fruitful results so far. We need a mechanism to alert the animals from crossing railway tracks when the train is approaching near. This paper proposes a simple and efficient technique which alerts animals about speeding trains. Unlike other techniques, our proposed mechanism does not need human intervention for operation.


Data mining Forest animals train accidents sensors vibration 


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  1. 1.
    Shu, T., Krunz, M.: Coverage-Time Optimization for Clustered wireless Sensor Networks: A Power-Balancing Approach. IEEE Transactions on Networking 18(1) (February 2010)Google Scholar
  2. 2.
    Ye, Z., Abouzeid, A.A., Ai, J.: Optimal Stochastic Policies for Distributed Data Aggregation in Wireless Sensor Networks. IEEE Transactions On Networking 17(5) (October 2009)Google Scholar
  3. 3.
    Xiang, M., Luo, Z., Wang, P.: Energy efficient intra-cluster data gathering in wireless sensor networks. Journal Of Networks (March 2010)Google Scholar
  4. 4.
    Ren, M., Guo, L.: Mining recent approximate frequent items in wireless sensor network. In: International Conference on Fuzzy Systems and Knowledge Discovery (2009)Google Scholar
  5. 5.
    Sin, I., Lee, J.: Performance analysis according to the change of cluster size in large scale wireless sensor networks. International Journal of Computer Science and Network Security (April 2009)Google Scholar
  6. 6.
    Pandey, S., Agarwal, P., Dong, S.: On Performance of Node Placement Approaches for Hierarchical Heterogeneous Sensor Networks. Springer, Heidelberg (2008)Google Scholar
  7. 7.
    Boukerche, A., Martiryosan, A., Pazzi, R.: An Inter-cluster Communication based Energy Aware and Fault Tolerant Protocol for Wireless Sensor Networks. Springer, HeidelbergGoogle Scholar
  8. 8.
    Watfa, M., Daher, W., Al Azar, H.: A Sensor Network Data aggregation technique. International Journal of Computer Theory and Engineering (1) (April 2010)Google Scholar
  9. 9.
    Bonivento, A., Fischione, C., Neechhi, L.: System level design of wireless sensor networks. Journal of Latex class files (6) (January 2007)Google Scholar
  10. 10.
    Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E.: A Survey on sensor networks. IEEE Communication Magazine 40(8), 102–114 (2002)CrossRefGoogle Scholar
  11. 11.
    Amis, A.D., Prakash, R.: Load-balancing clusters in wireless ad hoc networks. In: Proc. 3rd IEEE Symp. Application-Specific Syst. Software Eng. Technol., Richardson, TX, pp. 25–32 (2000)Google Scholar
  12. 12.
    Amis, A.D., Prakash, R., Vuong, T.H.P., Huynh, D.T.: Max-mind-cluster formation in wireless ad hoc networks. In: Proc. IEEE INFOCOM, Tel Aviv, Israel, pp. 32–41 (2000)Google Scholar
  13. 13.
    Baker, D.J., Ephremides, A.: The architectural organization of a mobile radio network via a distributed algorithm. IEEE Transactions on Commuication COM-29(11), 1694–1701 (1981)CrossRefGoogle Scholar
  14. 14.
    Bandyopadhyay, S., Coyle, E.J.: An energy efficient hierarchical clustering algorithm for wireless sensor networks. In: Proc. IEEE INFOCOM, San Francisco, CA, vol. 3, pp. 1713–1723 (2003)Google Scholar
  15. 15.
    Bandyopadhyay, S., Coyle, E.J.: Minimizing communication costs in hierarchically-clustered networks of wireless sensors. J. Computer Networks 44(1), 1–16 (2004)CrossRefGoogle Scholar
  16. 16.
    Boyd, S., Vandenberghe, L.: Convex Optimization. Cambridge Univ. Press, Cambridge (2004)zbMATHGoogle Scholar
  17. 17.
    Chiasserini, C.F., Chlamtac, I., Monti, P., Nucci, A.: An energy efficient method for nodes assignment in cluster-based ad hoc networks. J. Wireless Netw. 10(3), 223–231 (2004)CrossRefGoogle Scholar
  18. 18.
    Esveld, C., De Man, A.: Use of Railway Track Behaviour for Design and MaintenanceGoogle Scholar
  19. 19.
    Singh, A.K., Kumar, A., Mookerjee, A., Menon, V.: Jumbo Express- A scientific approach to understanding and mitigating elephant mortality due to train accidents. WTI (2001)Google Scholar
  20. 20.
    Athreya, V.R., Balssare, A.V.: Human-leopard conflict management guidelines (2007)Google Scholar
  21. 21.
    Joshi, R.: Train accidental Deaths Of LeopardsPanthera Pardus in Rajaji National Park: A Population in Threat. World Journal Of Zoology 5(3), 156–161 (2010)Google Scholar
  22. 22.
    De Man, A.P.: Dynatrack, a survey of dynamic railway track properties and their quality, Dissertation TU Delft, DUP-Science (December 2002) ISBN 9-406-2355-9Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • V. P. Jayachitra
    • 1
  • Sumalatha Ramachandran
    • 1
  1. 1.Madras Institute of TechnologyAnna UniversityIndia

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