FireGuard AI: An Intelligent Real-Time Fire Detection and Emergency Response System Using Computer Vision and Artificial Intelligence

FireGuard AI: Intelligent Real-Time Fire Detection and Emergency Response System FireGuard AI is a comprehensive, AI-powered fire detection and emergency response system designed to provide early fire identification, rapid alerting, and real-time guidance using computer vision and modern web technologies. The system addresses the limitations of traditional sensor-based fire detection systems by leveraging deep learning and software-based monitoring through standard webcam input. The core of the system utilizes the YOLOv5 object detection model, capable of identifying fire and smoke in real-time video streams with high accuracy and low latency. By analyzing live frames from a camera, the system can detect fire at an early stage, even before significant smoke accumulation, thereby enabling faster emergency response. In addition to detection, FireGuard AI integrates a Django-based web application that manages user registration, authentication, and administrative control. Users are required to register and obtain admin approval before accessing the system, ensuring secure and controlled usage. The platform provides a user dashboard for profile management, system monitoring, and interaction with the AI chatbot. A key feature of FireGuard AI is its multi-modal alert system. Upon detecting fire, the system immediately triggers: Voice alerts using text-to-speech technology for instant audible warnings Email notifications to all approved users with fire details and location links Visual alerts through bounding boxes and confidence scores displayed in real-time The system also includes an AI-powered chatbot built using Google Gemini, which provides real-time emergency guidance, fire safety instructions, and contextual assistance during critical situations. This enhances user awareness and helps in making informed decisions during emergencies. FireGuard AI is designed to run efficiently on standard consumer hardware without requiring specialized IoT devices, making it a cost-effective and accessible solution for homes, small businesses, and educational institutions. Its modular architecture allows easy scalability and future enhancements such as multi-camera support, mobile application integration, cloud deployment, and IoT-based automation. Key Features: Real-time fire detection using YOLOv5 Multi-modal alert system (voice, email, visual) AI chatbot for emergency guidance Web-based user and admin management system Cost-effective and hardware-independent deployment Scalable and modular architecture Technologies Used:Python, Django, PostgreSQL, OpenCV, YOLOv5, PyTorch, Google Gemini API, SMTP, pyttsx3 FireGuard AI demonstrates how artificial intelligence and computer vision can significantly enhance fire safety systems by providing faster detection, intelligent alerting, and real-time assistance. This project serves as a foundation for future smart safety systems and can be extended to integrate with smart cities and automated emergency response infrastructures.