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Fire-related incidents continue to rank among the most serious hazards in industrial, commercial, and residential settings. In many built environments, fires can intensify rapidly because of combustible materials, airflow patterns, and limited evacuation routes. Traditional fire protection systems are generally based on fixed-threshold detectors, standalone alarm panels, manual monitoring, and uniform suppression responses. While such systems provide a baseline level of safety, they may not perform effectively in complex structures such as hospitals, high-rise buildings, data centers, manufacturing facilities, and public institutions. In these environments, conventional approaches can lead to delayed detection of early fire indicators, frequent false alarms caused by harmless particles or temporary heat sources, and limited awareness of the evolving situation. As a result, response measures are sometimes poorly aligned with the actual progression of the fire or the movement of occupants within the building This study examines the potential of Artificial Intelligence (AI) to improve fire safety practices and suggests that AI- driven systems can move safety strategies from reactive response toward proactive and data-informed risk management. The discussion highlights several areas where AI can strengthen fire protection. First, AI can enhance alarm and sprinkler activation decisions by integrating data from multiple sensors and considering contextual factors, enabling more selective and accurate responses. Second, machine learning and computer vision techniques can assist in identifying early-stage signs of fire—such as unusual heat patterns, smoke behavior, or visible flames—particularly in high-risk zones where early detection is critical. Third, AI-based control systems can support more efficient suppression by adjusting the use of agents like carbon dioxide, foam, or water mist according to real-time assessments of fire intensity and spread. Fourth, evacuation strategies can be dynamically optimized through analysis of occupancy data and hazard conditions, helping occupants move along safer routes during emergencies. Finally, advancements in protective equipment, including flame-resistant gear equipped with environmental and physiological sensors, can provide alerts about hazardous exposure and assist in safeguarding emergency personnel.
Published in: International Journal of Advanced Research in Science Communication and Technology