Design and Development of a Multi-Extinguisher Autonomous Fire Fighting Robot

This paper presents the design and implementation of a multi-extinguisher autonomous firefighting robot that integrates machine learning, computer vision, and embedded systems for real-time fire detection and suppression. The system utilizes multiple camera modules to continuously monitor the environment and employs a deep learning-based approach to identify fire and smoke conditions. Based on the detection results, the system activates appropriate extinguishing mechanisms such as water spraying, mist generation, or mud application. A lightweight communication framework ensures efficient data exchange between system components, while a monitoring interface provides real-time system updates. The proposed system aims to reduce human involvement in hazardous firefighting environments and improve response efficiency. Experimental observations indicate reliable detection performance and acceptable response time, demonstrating the effectiveness of the system.