Forest fire danger early warning system based on Internet of Things communication

By using the feature fusion and communication optimization modules in the IoT communication system, the problems of accurate capture and noise stripping in the response to environmental changes in the forest fire risk early warning system were solved. This enabled high-precision fire point location and rapid data transmission under extreme fire conditions, ensuring early identification of forest fire risks and timely response from the decision-making center.

CN122135479AInactive Publication Date: 2026-06-02GUIZHOU XIANGYUAN TECH CO LTD
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Patent Information

Application Number
CN202610559878.1
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-04-27
Publication Date
2026-06-02
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

Existing technologies lack a deep separation mechanism for the steady state and abnormal fluctuations of the natural environment, making it impossible to accurately distinguish between normal meteorological disturbances and real fire plume thermal convection characteristics. This can easily lead to misjudging turbulent winds as fire turbulence, resulting in false alarms or missed alarms in early fire identification. In real fire scenes with a large amount of dense smoke obscuring the view, visible light images are full of noise, and there is a lack of dynamic adjustment capabilities to adaptively suppress visible light noise, which reduces the accuracy of fire location in complex scenarios.

Method used

A forest fire risk early warning system based on Internet of Things communication is adopted, including a data acquisition module, an environmental feature module, a feature fusion module, a feature inversion module, and a communication optimization module. The system obtains the environmental change response vector through the recursive method of adaptive forgetting factor, and combines dual-modal feature extraction and forced masking technology to construct the partial differential equation of canopy drag force and the inverse source-finding objective function, optimize the allocation of communication resources, and remove the flow field noise caused by natural random gusts.

Benefits of technology

It enables very early and accurate detection of small fire sources and reliable reporting with extremely low latency under extreme fire conditions, eliminates meteorological artifact interference, improves the accuracy of fire point location, avoids data packet collisions and channel congestion, and ensures rapid response of the decision-making center.

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Abstract

The invention discloses a forest fire danger early warning system based on Internet of Things communication, and relates to the technical field of data processing.The forest fire danger early warning system is characterized in that an acquisition module acquires forest region data of edge equipment; the environment feature module is used for obtaining an environment variation response vector in combination with a self-adaptive forgetting factor recursion method; the feature fusion module is used for extracting an image feature tensor, mapping the vector into a scaling matrix, weighting the feature tensor in combination with a forced mask and outputting a prediction frame parameter; the feature inversion module obtains a penalty matrix based on parameters, constructs a crown drag force partial differential equation, and solves a fire plume feature matrix and a flow field uncertainty tensor matrix through a minimization reverse source searching objective function; and the communication optimization module extracts elements from the fire plume elements as fire danger mapping weights, sorts the fire plume elements in a descending order and allocates time resources, so that the terminal only sends the fire plume elements to a decision center. According to the method, meteorological interference can be effectively stripped, the positioning precision of the micro fire point under dense smoke is improved, and the problem of communication congestion during extreme fire concurrence is solved.
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