Natural Disaster Sustainability Forest Fire Detection System Based on Computer Vision Using Smart IoT Sensor Networks and Deep Learning Techniques

Forest Fire pose significant threats to ecosystems, human life, and property. Early detection and rapid response are crucial for effective firefighting and mitigation efforts. In this paper, we propose a novel forest fire detection system leveraging smart sensor networks and deep learning techniques. Our system employs computer vision algorithms to analyze real-time video feeds from strategically placed cameras in forested areas. Deep learning models, particularly convolutional neural networks (CNNs) and Artificial Neural Networks (ANNs) are utilized to detect and classify fire-related patterns in the video streams. The proposed system aims to enhance the speed and high accuracy of forest fire detection, thereby enabling prompt intervention and minimizing the devastating impacts of such natural disasters. The accuracy and efficiency results produced ANN is 89% and CNN is 95%. This technology is used to minimize forest fire losses.