Intelligent identification method for classifying intrusion events in security areas

By acquiring regional security weights and monitoring bus load rates, dynamically calculating instruction scheduling priorities, and driving high-speed cache fast channel processing, the problem of instruction stream congestion and latency caused by static resource scheduling in multi-channel heterogeneous monitoring pixel feature tensor streams is solved, achieving efficient data processing and eliminating the risk of buffer overflow.

CN122394964APending Publication Date: 2026-07-14XIAN YINUO DEDICATED ELECTRONIC TECH CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
XIAN YINUO DEDICATED ELECTRONIC TECH CO LTD
Filing Date
2026-06-12
Publication Date
2026-07-14

AI Technical Summary

Technical Problem

Existing technologies, when processing multi-channel heterogeneous monitoring pixel feature tensor streams, suffer from static resource scheduling, which leads to instruction stream congestion and high latency in key feature identification. They are unable to cope with complex and ever-changing physical space feature disturbances and cannot effectively eliminate the risk of buffer overflow.

Method used

By acquiring regional security weights, extracting feature perturbation offsets and monitoring bus load rates, dynamically calculating instruction scheduling priorities, driving high-speed cache fast channel processing, and combining deep residual networks to update adaptive thresholds, dynamic arbitration and optimized scheduling of resources are achieved.

Benefits of technology

It realizes the dynamic perception and logical evolution of processing resources, eliminates the contradiction between resource idleness and instruction accumulation, ensures the system's ability to prioritize the parsing of high-risk data under extreme overload conditions, and improves the system's robustness and processing efficiency.

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Abstract

The present application belongs to the field of security monitoring digital signal processing technology, and relates to a kind of hierarchical security area invasion event intelligent identification method, comprising: obtaining the security weight score of the region to be identified;Sampling video signal and generating stream data message composed of binary bit stream;Compare adjacent data frames to extract feature disturbance offset;Real-time monitoring of the instantaneous load rate of data bus;Coupling weight score and feature disturbance offset, introduce instantaneous load rate to calculate the task scheduling priority of stream data message;When the task scheduling priority exceeds the dynamic adaptive threshold, drive the central processor to start the fast processing channel based on level 1 cache prefetching, the present application dynamically adjusts the data access threshold through the load feedback mechanism, effectively eliminates the risk of buffer overflow, and enhances the high-risk data priority analysis capability of the system under extreme overload working conditions.
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