Forest Fire Detection using Nine-Layer Deep Convolutional Neural Network

Abstract

Forest fires (FF) may endanger human life and ecological, environmental, and natural resource systems. However, such disasters can be lessened, and an automated early FF detection surveillance system can protect the ecosystem. We proposed a FF fighting system and created a nine-layer deep convolutional neural network to discern between photographs of fire and no fire. The suggested model achieves 96.71% classification accuracy following rigorous simulation. The recommended work is more accurate than the earlier work.