Coal Burn Detection using Wireless Sensor Network with Evidence Combination
M.Syed Mohamed1, M.Mohamed Sathik2, K.Senthamarai Kannan3

1M.Syed Mohamed, Research Scholar, Manonmaniam Sundaranar University, Tirunelveli, Tamilnadu, India.
2M.Mohamed Sathik, Principal, Sadakkathullah Appa College, Tirunelveli, Tamilnadu, India.
3K.Senthamarai Kannan, Professor, Dept. of Statistics, Manonmaniam Sundaranar University, Tirunelveli, Tamilnadu, India.
Manuscript received on November 01, 2012. | Revised Manuscript received on November 02, 2012. | Manuscript published on November 05, 2012. | PP: 35-38 | Volume-2 Issue-5, November 2012. | Retrieval Number: E0988092512/2012©BEIESP
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Abstract: It is a well known fact that the coal required for the operation of the Thermal Power Plants is stored in a Coal Yard. But, the difficulty of using the Coal yard is the nature of the self burning of the coal. At atmospheric temperature, the coal burns itself and becomes ash reducing the quality of the coal. A lot of de–ashing methods are available such as pouring water which further reduces the quality of coal. The present method of deashing by adding water in large quantity leads to decrease the quality of coal. Hence, it is necessary to detect and predict fire in Coal yard more promptly and accurately to minimize the quality of coal. This paper introduces an efficient and intelligent smart system for coal fire detection using wireless sensor network with evidence combination.
Keywords: Coal burn, SVM, Dempster Shafer , Classifer, Wireless Sensor Network.