Intelligent analysis of influencing factors for urban fire risk and hazard investigation
List of Authors
  • Bin Deng , Xingrong Tang

Keyword
  • Fire Risks, Risk Factors, You Only Look Once, Hazard Detection, Efficiency

Abstract
  • The management of fire risks has become an important challenge for urban safety. Traditional methods of fire hazard detection have the problems of low efficiency and insufficient accuracy, while intelligent means, especially target detection technology based on deep learning and You Only Look Once (YOLO), provide new solutions for the investigation of urban fire risks and hazards. This study conducts intelligent analysis of urban fire hazards based on the YOLO algorithm and constructs a fire hazard identification system (FHIS). Through literature review, data collation, model training and actual testing, this paper realizes the identification of key influencing factors of urban fire risks in China. The results show that the system is superior to traditional methods in detection accuracy and speed and improves the efficiency of fire hazard detection, including building types, population density, fire protection facilities and fire management. Therefore, FHIS provides a scientific basis for future urban safety management.

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