SMART FIRE DETECTION AND ALERT SYSTEM FOR BUILDINGS

Abstract

The Smart Fire Detection and Alert System for Buildings is an AI-enabled intelligent monitoring solution designed to enhance early fire detection, risk assessment, and emergency response in residential, industrial, and commercial environments. The proposed system integrates IoT-based environmental sensors, real-time temperature and smoke monitoring, and machine learning–based anomaly detection algorithms to accurately identify potential fire hazards. The system continuously collects data from multiple sensors, including temperature, gas, humidity, and smoke detectors, and processes it using predictive analytics to distinguish between normal environmental variations and critical fire conditions.Upon detecting abnormal patterns, the system automatically triggers instant alerts through mobile notifications and alarm systems while simultaneously notifying emergency services if required. Cloud-based data storage ensures centralized monitoring, historical data analysis, and remote accessibility. The system is developed using modern embedded systems and web technologies to ensure scalability, low latency, energy efficiency, and cross-platform integration.Experimental evaluation conducted in a controlled environment demonstrates improved fire detection accuracy exceeding 95%, reduced false alarm rates by approximately 30–40%, and faster response times compared to conventional fire alarm systems. User feedback highlights enhanced safety, reliability, and real-time monitoring capabilities. The results validate the effectiveness of AI-driven automation in improving disaster prevention, public safety, and infrastructure protection, demonstrating its potential for deployment in smart homes, smart cities, and industrial safety systems.