Abstract: The use of wooden structures as the main structure in ancient buildings has led to frequent human caused fires. Due to the large and long-term ignition, burning, and other situations in ancient buildings for worship, lighting, or creating an atmosphere, it seriously interferes and affects the conventional point type smoke detectors, suction type, linear light beams, and image type fire detectors installed inside the building, resulting in a high false alarm rate. Therefore, this article proposes a new method for identifying controlled fire interference in ancient buildings based on artificial intelligence image processing technology, aiming at the technical difficulties of fire early warning and detection in large spaces inside large ancient buildings. Through the design of fire intelligent detection algorithms and controlled fire intelligent identification and confirmation algorithms, the intelligent identification of "behavior" image features of real fires and controlled fires in typical scenarios is achieved. The experimental results show that this method can provide warning prompts for both real and controlled fires within 4 s, effectively solving the technical difficulties of fire prevention and control in large ancient buildings.

Key words: fire detection, ancient architecture, controlled fire, deep learning