主管:中华人民共和国应急管理部
主办:应急管理部天津消防研究所
ISSN 1009-0029  CN 12-1311/TU

消防科学与技术 ›› 2025, Vol. 44 ›› Issue (9): 1320-1325.

• • 上一篇    下一篇

基于火灾风险监测预警大数据模型的消防安全综合监管探索

安春晖   

  1. (天津市消防救援总队,天津 300090)
  • 收稿日期:2025-07-30 修回日期:2025-08-08 出版日期:2025-09-15 发布日期:2025-09-15
  • 作者简介:安春晖,天津市消防救援总队总队长,主要从事灭火救援及消防安全管理工作,天津市南开区南马路708号,300090,772411053@qq.com。

Exploration of comprehensive fire safety supervision based on fire risk monitoring and early warning big data model

An Chunhui   

  1. (Tianjin Fire and Rescue Brigade, Tianjin 300090, China)
  • Received:2025-07-30 Revised:2025-08-08 Online:2025-09-15 Published:2025-09-15

摘要: 面对消防监督力量薄弱、传统监管模式滞后、多源数据融合困难及监管效能不足等挑战,天津市消防救援总队(以下简称天津总队)积极响应国家发展新质生产力和大数据战略的要求,以打造新质战斗力为目标,研发了火灾风险监测预警系统,用于引领和指导全市消防安全综合监管工作。本文系统阐述了天津总队依托国家超级计算中心等技术力量,以大数据为基础,以AI智算为支撑,建立了细粒度的火灾风险预警模型、消防领域大模型、火灾风险溯源模型,并融合多维实时监测数据,实现了预警信息向属地、行业、专业监管主体的精准推送与穿透落实,显著提升了风险识别精度、监管资源配置效率及隐患整改闭环率,为构建科学高效的消防安全综合监管体系、推动治理模式向“事前预防”转型提供了有力支撑。

关键词: 火灾风险监测;智能火灾预警;大数据;消防监督管理

Abstract: Faced with challenges such as weak fire supervision forces, outdated traditional supervision models, difficulties in multi-source data fusion, and insufficient regulatory efficiency, the Tianjin Fire and Rescue Brigade actively responded to the requirements of the national development of new quality productivity and big data strategy, with the goal of creating new quality combat effectiveness, and developed a fire risk monitoring and early warning system to lead and guide the comprehensive supervision of fire safety in the city. This article systematically elaborates on the establishment of a fine-grained fire risk warning model, a large model in the field of fire protection, and a fire risk traceability model by the Tianjin Fire and Rescue Brigade, relying on the technical strength of the National Supercomputing Center and other technologies, with big data as the foundation and AI intelligent computing as the support. It also integrates multidimensional real-time monitoring data to achieve precise push and penetration of warning information to local, industry, and professional regulatory entities, significantly improving the accuracy of risk identification, the efficiency of regulatory resource allocation, and the closed-loop rate of fire hazard rectification. This provides strong support for building a scientific and efficient comprehensive fire safety supervision system and promoting the transformation of governance to "pre-vention" mode.

Key words: fire risk monitoring; intelligent fire warning; big data; fire supervision and management