A Smart Forest Fire Detection and Notification System using IOT and Machine Learning

In this paper, the proposed system presents a two-stage forest fire detection system that first uses a wireless sensor network of MQ sensors and a Node MCU and then a YOLOv8 forest fire detection model to reduce false alarms. The entire process is seamlessly integrated with the Raspberry Pi, which immediately triggers an email notification for quick action upon receiving confirmation of a fire. As the frequency and severity of wildfires continue to escalate, it is imperative that we take swift action to address their devastating impact. The YOLO model was able to achieve an accuracy of 92% with low power and memory consumption on the MCU. The method serves as a demonstration of the potential of combining innovative technologies to solve environmental problems and contributes to the development of effective and proactive fire detection systems using IOT and Machine learning.