Intelligent fire-fighting closed-loop management method and system based on multistage early warning and six-stage linkage

The intelligent fire management system, with its multi-level early warning and six-level linkage, solves the problems of single perception, rigid early warning, and disconnected response in traditional fire protection systems. It enables accurate assessment and dynamic response to fire risks, thereby improving the level of intelligence in fire prevention and control.

CN121660468AInactive Publication Date: 2026-03-13XINJIANG WENTENG INFORMATION TECH CO LTD
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Patent Information

Application Number
CN202511862282.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-12-11
Publication Date
2026-03-13
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

Traditional fire safety systems suffer from insufficient overall fire prevention and control effectiveness due to their limited perception capabilities, rigid early warning systems, disconnect between response and real-time risk situation, and lack of learning and evolution mechanisms.

Method used

By deploying multiple sensors to acquire multi-source sensing data, using a fire risk analysis model for deep learning processing, a comprehensive fire risk index is generated, the warning level is dynamically adjusted and a six-level linkage response plan is initiated, and the model is corrected through feedback information to form a closed-loop management system.

Benefits of technology

It enables early and accurate assessment of fire risks, ensuring the accuracy and timeliness of early warning and response, and improving the intelligence level and overall effectiveness of fire prevention and control.

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Abstract

The invention relates to the technical field of fire-fighting management, in particular to an intelligent fire-fighting closed-loop management method and system based on multistage early warning and six-stage linkage, and the method comprises the steps: firstly, obtaining multi-source sensing data, generating a comprehensive fire risk index through a fire risk analysis model, and achieving the precise risk assessment; a threshold value is dynamically adjusted by combining a real-time environment and a historical model so as to determine a multi-level early warning level, and intelligent and accurate early warning is ensured; starting a corresponding six-level linkage response scheme according to the early warning level, predicting a fire behavior and dynamically optimizing a response strategy according to a risk index change trend, and synchronizing an emergency decision and a real-time risk situation; and finally, a closed-loop management system integrating intelligent sensing, dynamic early warning, self-adaptive linkage and continuous optimization is formed by executing a feedback correction analysis model, and the fire prevention and control efficiency is comprehensively improved.
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