IoT-based early forest fire detection using MLP and AROC method

The forest is a natural ecosystem that must be protected against natural calamities. Forest fire is one such calamity, and the goal of this work is to alert the event of disaster so that natural resources can be saved. The existing methods have few limitations like false alert, no timely notification, lack of network coverage, etc. The proposed work uses multi-layer perceptron (MLP) and advanced relative operating characteristic (AROC) approaches to address these constraints. The proposed model has accuracy of 90%, which is higher than the fuzzy logic and average consensus algorithm.