FireFighterX: Detecting and Preventing Forest Fires with an Artificial Intelligence-Enabled Autonomous Vehicle
FireFighterX: Detecting and Preventing Forest Fires with an Artificial Intelligence-Enabled Autonomous Vehicle

Summary/Abstract: This study presents the development of FireFighterX, an autonomous fire extinguishing vehicle equipped with Artificial Intelligence (AI)-powered image processing techniques. The system employs an ESP32-CAM module and a deep learning-based Convolutional Neural Network (CNN) model for real-time fire detection, while Arduino-controlled motors enable autonomous navigation and a water-spraying system for intervention. Experimental tests demonstrated a 94% detection accuracy, rapid response, and effective fire suppression. The CNN model, trained with the binary cross-entropy loss function and Adam Optimizer, achieved low error rates and high learning performance. With its low-cost, modular design and adaptability to diverse geographical conditions, FireFighterX represents a significant advancement in automation and efficiency for firefighting, emerging as a promising solution for integration into global disaster management strategies.

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