Wildfire Risk Assessment and Detection for Remote Terrain

The Wildfire Risk Assessment and Detection for Remote Terrain project presents an intelligent monitoring system designed to detect and predict wildfire hazards using real-time environmental data. The system employs sensors such as the DHT11 for measuring temperature and humidity, the MQ-2 sensor for detecting smoke and combustible gases, and a soil moisture sensor to assess ground dryness, which is a critical factor in fire risk prediction. A microcontroller like the Arduino Uno or ESP32 collects and processes the sensor data to identify abnormal conditions such as high temperature, low humidity, presence of smoke, and low soil moisture levels. When these parameters exceed predefined thresholds, the system generates alerts through a buzzer and sends notifications via a GSM module, while also uploading data to cloud platforms like ThingSpeak for remote monitoring and analysis. This integrated approach enables early warning, improves response time, and reduces the risk of large-scale wildfire damage, making the system suitable for forest surveillance and remote terrain safety applications.