A Survey On Machine Learning Techniques Used in Tracking Livestock in Rural Areas using Wireless Sensor Networks
Journal Title: International Journal of Electronics Communication and Computer Technology - Year 2015, Vol 5, Issue 1
Abstract
There are many countries where livestock plays a major role in the country’s economy and livelihood for the people in the country. Wireless Sensor Network (WSN) can be a good potential for implementing tracking and monitoring systems. However, wireless sensors have limitations. Some researches have been done on using machine learning techniques to develop WSNs. This paper presents a survey on some machine learning techniques and other techniques found in literature to track livestock using WSNs. The most widely used location tracking method for livestock currently used is Global Position System (GPS). One alternate technique of tracking is through using localisation algorithms. Some machine learning techniques have still not been exploited to develop localization algorithms for tracking livestock. Application specific localisation algorithms can be developed using machine learning. Some of the characteristics that need to be considered when developing application specific localisation algorithms for WSNs are the technical characteristics of the nodes; the livestock characteristics such as living and moving characteristics; and area (geographic) characteristics of deployment
Authors and Affiliations
Sajid M. Sheikh| Department of Electrical Engineering University of Botswana, Gaborone, Botswana
Keywords
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