Edge computing and decision-based incident response method, system, device, and medium

By performing dual-channel feature fusion of runtime data and environmental data and dynamic decision network processing on edge computing nodes, the problems of false alarms and missed alarms in edge event response are solved, achieving high-precision, low-latency event response control and enhancing the robustness and flexible adaptive capabilities of edge computing.

CN122653945APending Publication Date: 2026-08-28HAINAN STRAIT SHIPPING CO LTD
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Patent Information

Application Number
CN202611042950.X
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-07-14
Publication Date
2026-08-28

AI Technical Summary

Technical Problem

Existing edge event response methods are prone to false alarms or missed alarms when faced with complex, variable, and noisy multidimensional time-series data streams. They cannot accurately define the effective rule boundaries of response strategies, resulting in delayed response actions, premature termination, or over-response, and cannot meet the requirements of high-precision, deterministic, and rapid closed-loop control.

Method used

By acquiring operational data and environmental data for dual-channel feature fusion, using state space segmentation to filter out background interference, employing a dynamic decision network to generate dynamic constraint boundaries for response candidate strategies, identifying associated points through temporal difference operators and sequence topology analysis, and combining Kalman filtering algorithm for trajectory prediction and multi-dimensional data fusion correction, flexible adaptive adjustment is achieved.

Benefits of technology

It effectively filters out background noise interference, accurately separates high-risk areas of event anomalies, and realizes the anti-disturbance capability and decision robustness of edge computing nodes under extreme working conditions. It ensures ultra-low latency and high accuracy of event response, and has support for complex semantic reasoning and security fault tolerance boundaries at both the software and hardware levels.

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Abstract

The application provides an event response method, system, device and medium based on edge computing and decision, the method comprising: obtaining running data and environment data of a target system; performing double-channel feature fusion on the running data and the environment data, filtering out background interference through state space segmentation to separate out an event abnormal high-risk area; inputting a feature matrix corresponding to the event abnormal high-risk area into a dynamic decision network to generate a dynamic constraint boundary of a response candidate strategy; calculating a multi-dimensional trend difference of the running data using a time series difference operator, filtering the multi-dimensional trend difference using a double threshold to separate out strong correlation points and weak correlation points, and identifying linear topological structures of the strong correlation points and the weak correlation points using a sequence topological analysis algorithm to extract time series direction features; drawing a decision evolution reference line in a state space according to the time series direction features; and solving two space-time intersection points of the decision evolution reference line and the dynamic constraint boundary as a starting trigger point and a termination cutoff point of event response execution, respectively.
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