Development of an Autonomous Unmanned Ground Vehicle System for Forest Fire Detection and Exploration with Multi-Sensor Fusion and Web-Based Control

The increasing frequency and intensity of forest fires have necessitated the development of advanced technologies for early detection and assessment of fire hazards. Unmanned Ground Vehicles (UGVs) equipped with multi-sensor systems offer a promising solution for exploring hazardous areas and providing real-time data on fire conditions. This paper presents a UGV control system based on the Raspberry Pi 4B, integrating ultrasonic sensors, infrared sensors, CSI cameras, MG995 servos, and TB6612FNG motor drivers. The system is designed to achieve four primary objectives: ultrasonic obstacle avoidance, infrared obstacle avoidance, automatic fire recognition, and remote control. By leveraging multi-sensor data fusion and intelligent control algorithms, the UGV can autonomously navigate through forest environments, detect fire hazards, and assess the scale of the fire. The system serves as a foundational model for deploying UGVs in forest fire exploration, providing a safe and efficient alternative to human intervention in dangerous scenarios. Experimental results demonstrate the system's effectiveness in obstacle avoidance, fire detection, and remote control, highlighting its potential for real-world applications in disaster response and environmental monitoring.