Method for evaluating county fire risk and fire safety based on big data

By constructing a multi-level risk profiling framework, simulating the chain-triggered scenarios of disaster-causing factors, deducing the risk state migration path, and optimizing the risk profile by combining real-time monitoring signals, a dynamic spectrum of county-level fire risk is generated. This solves the limitations of existing risk assessment methods and realizes a systematic, structured understanding and dynamic prediction of county-level fire risk.

CN122114355APending Publication Date: 2026-05-29CIXI FIRE RESCUE BRIGADE (CIXI FIRE RESCUE BUREAU)
View PDF 0 Cites 0 Cited by

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
CIXI FIRE RESCUE BRIGADE (CIXI FIRE RESCUE BUREAU)
Filing Date
2026-01-23
Publication Date
2026-05-29

AI Technical Summary

Technical Problem

Existing county-level fire risk assessment methods fail to effectively reflect the intrinsic connections between risk factors and the coupling effect of the external dynamic environment, making it difficult to achieve forward-looking prediction of risk transmission paths and accurate positioning of high-risk situations.

Method used

Based on big data, a multi-level risk profiling framework is constructed. By acquiring time-stamped building basic information, fire resource allocation and fire case data, the system simulates the chain-triggered scenarios of disaster-causing factors, deduces the risk state migration path and evolution stage, integrates real-time monitoring signals to optimize the risk profile, and generates a dynamic spectrum of county-level fire risks.

Benefits of technology

It achieves a systematic and structured in-depth understanding of county-level fire risks, dynamically reveals the risk transmission and amplification mechanisms, proactively identifies high-risk evolution clusters, and provides decision-making information for intervention measures.

✦ Generated by Eureka AI based on patent content.

Smart Images

  • Figure CN122114355A_ABST
    Figure CN122114355A_ABST
Patent Text Reader

Abstract

The application discloses a county fire risk and fire safety dynamic evaluation method based on big data, relates to the technical field of fire safety risk evaluation, and comprises the following steps: acquiring and processing building, fire resources and historical fire data with time identifiers to form a clean data pool. Based on hierarchical rules, the symbiotic law of risk elements in each level and the coupling relationship between the risk elements and the external environment are identified to construct a multi-level risk portrait. By simulating the chain triggering scenarios of different disaster-causing factors, the risk state migration path and evolution stage are deduced, the high-risk evolution cluster is located, and the core parameters thereof are iteratively optimized. The optimized parameters and real-time monitoring signals are fused to dynamically update the portrait and generate a fire risk dynamic spectrum. The method realizes the transformation from static evaluation to process prediction by depicting the risk correlation network and simulating the dynamic evolution process, and improves the systematicness and foresight of risk early warning.
Need to check novelty before this filing date? Find Prior Art