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Enhancement of Animal Tracking by Means of Wireless Sensor Network Using Machine Learning Technique

Ayatollahi, Azarm | 2011

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  1. Type of Document: M.Sc. Thesis
  2. Language: English
  3. Document No: 41732 (52)
  4. University: Sharif University of Technology, International Campus, Kish Island
  5. Department: Science and Engineering
  6. Advisor(s): Bagheri Shouraki, Saeed; Ghorshi, Mohammad Ali
  7. Abstract:
  8. A Wireless Sensor Network is one of the attended research context that is used to meet different requirements of a wide range of applications. One of the usages of WSNs is in Animal Tracking. Many Animal Tracking methods have weaknesses that can be enhanced. By considering WSN properties and many different usages of Machine Learning techniques reported in a variety of fields and considering Animal Tracking methods characteristics, WSNs can be improved by applying Machine Learning techniques. The main goal of this thesis is to show that with help of Machine Learning techniques, performance of Animal Tracking by means of Wireless Sensor Networks increases. To fulfill this goal, we first evaluate the energy amount of reporting the information of animal movement detection to base station, and calculate the amount of energy used for routing this data in Wireless Sensor Networks while all the sensor nodes are awake and ready to detect. In the next step with the use of Machine Learning techniques we powered off some of the nodes that did not detect any event in the first step periodically, and again route the message of detection through the network such that nodes which detect movement did not involve in routing. Evaluating the amount of energy used in the second approach and comparing it with the fist one clearly show that the Machine Learning techniques can be successfully applied to the Animal Tracking approach with the use of WSNs.
  9. Keywords:
  10. Wireless Sensor Network ; Machine Learning ; Routing ; Animal Tracking

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