CFP last date
20 March 2024
Reseach Article

Rare Wild Animal Tracking in the Forest area with Wireless Sensor Network in Network Simulator-2

by Sanjyot S. Ghumare, Rekha P. Labade, Sunil R. Gagare
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 133 - Number 4
Year of Publication: 2016
Authors: Sanjyot S. Ghumare, Rekha P. Labade, Sunil R. Gagare
10.5120/ijca2016907415

Sanjyot S. Ghumare, Rekha P. Labade, Sunil R. Gagare . Rare Wild Animal Tracking in the Forest area with Wireless Sensor Network in Network Simulator-2. International Journal of Computer Applications. 133, 4 ( January 2016), 1-4. DOI=10.5120/ijca2016907415

@article{ 10.5120/ijca2016907415,
author = { Sanjyot S. Ghumare, Rekha P. Labade, Sunil R. Gagare },
title = { Rare Wild Animal Tracking in the Forest area with Wireless Sensor Network in Network Simulator-2 },
journal = { International Journal of Computer Applications },
issue_date = { January 2016 },
volume = { 133 },
number = { 4 },
month = { January },
year = { 2016 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume133/number4/23771-2016907415/ },
doi = { 10.5120/ijca2016907415 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:30:10.050276+05:30
%A Sanjyot S. Ghumare
%A Rekha P. Labade
%A Sunil R. Gagare
%T Rare Wild Animal Tracking in the Forest area with Wireless Sensor Network in Network Simulator-2
%J International Journal of Computer Applications
%@ 0975-8887
%V 133
%N 4
%P 1-4
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

To keep of track wild animal in forest area is very difficult task. As one cannot go to the deep inside forest, as no one wants to jeopardize one’s life. Use of Wireless sensors in such areas is best solution. As these sensors only have to put in one place and after that they self-organize their position in the given or programmed area. To track an animal Localization is very important factor. As if the position of the sensor nodes are known in the sensor network, it is easy to identify position of an animal in that network. In wireless sensor network energy saving is also an important factor for networks lifetime. Here clustering algorithm is using to save energy in the nodes which is Low Energy Adaptive Clustering Hierarchy along with prediction operation in the area. Spatial resolution is also measure in this simulation for checking accuracy in the animal tracking.

References
  1. Chi-ChangChen, Chi-YuChang and Yan-NongLi, “Range-Free Localization Scheme in Wireless Sensor Networks Based on Bilateration,” p. 10, 2013.
  2. Himakshi and C. K. Singh, “A Review: Wireless Sensor Networks Application and Technology,” International Journal of Computing & Business Research, 2012.
  3. E. Xu, Z. Ding and S. Dasgupta, “Target Tracking and Mobile Sensor Navigation in Wireless Sensor Networks,” in IEEE transactions on mobile computing, 2013.
  4. G. Raghunandan and B. Lakshmi, “A Comparative Analysis of Routing Techniques for Wireless Sensor Network,” in Proceedings of the National Conference on Innovations in Emerging Technology, 2011.
  5. Sikora and E. Niewiadomska-Szynkiewic, “Mobility Model for Self-Configuring Mobile Sensor Network,” in International Conference on Sensor Technologies and Applications, 2011.
  6. V. P. Sadaphal and B. N. Jain, “Tracking mobile target using selected sensors,” 2014.
  7. E. T. Yazdi, A. Moravejosharieh and S. K. Ray, “Study of Target Tracking and Handover in Mobile Wireless Sensor Network,” in IEEE ICOIN, 2014.
  8. J. Suh, S. You and a. S. Oh, “A Cooperative Localization Algorithm for Mobile Sensor Networks,” in 8th IEEE International Conference on Automation Science and Engineering, Seoul, Korea, 2012.
  9. B. Zack and R. Daniela, “Event-Based Motion Control for Mobile- Sensor Networks,” in Published by the IEEE CS and IEEE ComSoc, 2003.
  10. G. Y. Keung, B. Li, Q. Zhang and H.-D. Yang, “The Target Tracking in Mobile Sensor Networks,” Networking, 2013.
Index Terms

Computer Science
Information Sciences

Keywords

Animals Trajectory finder Prediction clustering NS-2.