"Real-Time Forest Fire Detection Using FireNet-CNN and Explainable AI Methods"

Computer Engineering

Forest fires are one of the most devastating natural disasters, posing significant threats to ecosystems, biodiversity, and human life. Early detection of forest fires is crucial for mitigating these impacts. In this research, we present a novel framework for real-time forest fire detection using FireNet-CNN, a deep convolutional neural network (CNN) model, alongside Explainable AI (XAI) techniques to enhance model transparency and decision-making. The proposed system leverages satellite imagery and sensor data to detect fires quickly and efficiently while providing interpretable results to assist emergency responders. We evaluate the system’s performance using real-world datasets and discuss its potential impact on improving disaster management.

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