Real-Time Forest Fire Detection Using IoT and Smart Sensors

Forest fires provide a serious risk to the natural world and human lives, making effective detection and response essential. This research study presents a smart sensor-based IoT forest fire detection system that focuses on machine learning methods. To detect and categorize forest fires in real-time, the proposed system combines data from sensors, including temperature sensors and smoke detectors. The proposed system performance is assessed by using a labeled dataset and explaining the algorithms' advantages and disadvantages, including potential difficulties and constraints for forest fire detection. This study also proposes future work to address these challenges and enhance the suggested system's performance. This research study contributes to the creation of reliable and effective innovations to identify wildfires that leverage the power of machine learning algorithms and highlights the need for continued research and development in this important area.