Real-Time Forest Fire Detection Using ESP32 Microcontroller with Cloud-Integrated Monitoring System

This research article offers an innovative approach for detecting forest fires in real time by integrating environmental sensors with ESP32 microcontroller nodes. These nodes continuously monitor critical parameters such as temperature, humidity, and smoke levels, serving as an initial defence against wildfires. The system utilises master-slave architecture to efficiently collect and transmit data to a cloud platform. This enables remote access for authorized personnel to monitor sensor readings in real-time and configure alerts from anywhere with internet connectivity. By incorporating machine learning algorithms to analyse historical data, the system can identify fire risk patterns swiftly and accurately. This capability facilitates proactive measures to mitigate potential outbreaks, thereby minimizing ecological damage and ensuring firefighter safety. The system's scalability allows for deployment over extensive forest areas, establishing a comprehensive and intelligent network for early fire detection and response.