CNN Based Real-Time Fire Detection System

The early detection and rapid response to fires are vital in minimizing damage and protecting lives and property. This study presents a camera-based fire detection system utilizing advanced image processing techniques and Artificial Intelligence (AI). The system, employing Convolutional Neural Networks (CNNs) for image analysis, achieves an accuracy rate of 89% in detecting fire. Upon detection, the system sends real-time notifications to users through Telegram, enabling swift intervention and enhancing emergency response times. This approach significantly improves fire detection capabilities, particularly in large, complex environments where traditional detection methods are less effective. The integration of CNN-based image processing with communication technologies such as Telegram bots provides a flexible, accessible, and scalable solution. The proposed system demonstrates its potential as an innovative tool for enhancing fire safety and response efficiency, ensuring timely intervention and minimizing the impact of fires.