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<p>Mobile smart devices enhance social perception capabilities in the era of the Internet of Things. These intelligent sensors can be used to collect and upload risk information to support smart urban risk management in intelligent city management system. Drawing on risk data aggregated by the system and grounded in environmental criminology theory, this study develops an analytical framework to examine the relationship between urban building fire hazards and their key influencing factors. The study empirically tests this framework using spatial error modeling, based on data from Shenzhen’s Guangming District Digitized Urban Management System, which covers three common fire hazards: unsafe storage of flammable materials, improper installation and use of electrical equipment, and unsafe charging of electric bicycles. The results indicate that individual characteristics, environmental conditions, and the absence of effective guardianship jointly contribute to the occurrence of fire hazards, with leading factors varying significantly across different hazard types. By utilizing high-resolution hazard data collected via mobile smart devices, this research overcomes the limitations of coarse, macro-level data common in traditional fire studies and promotes a paradigm shift in fire management from&#xa0;post-incident response&#xa0;to&#xa0;pre-ignition prevention. The findings not only bridge fire prevention strategies with daily urban safety management but also provide empirical evidence and decision-making support for building a data-driven, cross-departmental proactive risk prevention system within smart city governance.</p>

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Examining the Influencing Factors of Urban Fire Dangers Based on Environmental Criminology Theories

  • 期刊论文

  • 发表日期：

    2026年4月24日

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  • Liuchen Song,
  • Cong Liao

摘要

Mobile smart devices enhance social perception capabilities in the era of the Internet of Things. These intelligent sensors can be used to collect and upload risk information to support smart urban risk management in intelligent city management system. Drawing on risk data aggregated by the system and grounded in environmental criminology theory, this study develops an analytical framework to examine the relationship between urban building fire hazards and their key influencing factors. The study empirically tests this framework using spatial error modeling, based on data from Shenzhen’s Guangming District Digitized Urban Management System, which covers three common fire hazards: unsafe storage of flammable materials, improper installation and use of electrical equipment, and unsafe charging of electric bicycles. The results indicate that individual characteristics, environmental conditions, and the absence of effective guardianship jointly contribute to the occurrence of fire hazards, with leading factors varying significantly across different hazard types. By utilizing high-resolution hazard data collected via mobile smart devices, this research overcomes the limitations of coarse, macro-level data common in traditional fire studies and promotes a paradigm shift in fire management from post-incident response to pre-ignition prevention. The findings not only bridge fire prevention strategies with daily urban safety management but also provide empirical evidence and decision-making support for building a data-driven, cross-departmental proactive risk prevention system within smart city governance.