An efficient and optimal clustering algorithm for real-time forest fire prediction with

Grouping of forest fire images into meaningful categories to reveal useful information is a challenging task. In order to overcome this challenge, data mining techniques can be used with wireless sensor network which can detect and forecast forest fire more promptly than the satellite-based detection approach. This paper proposes an efficient image clustering algorithm using real time data for predicting of the occurrence of forest fire, with a new mechanism for secure information transmission in wireless sensor networks by minimizing the threat attacks caused by malicious nodes in wireless sensor networks.

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