Method for monitoring and identifying dangerous behaviors of smart park

By deploying sensing devices and edge computing in the park, combined with lightweight target detection and a 3D credibility fusion model, the problems of low efficiency and high false alarm rate of traditional park monitoring systems have been solved, enabling proactive early warning and precise prevention and control, and improving the intelligence and response efficiency of the security system.

CN121744262APending Publication Date: 2026-03-27ANHUI HEXIN TECH DEV
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Patent Information

Application Number
CN202511947669.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-12-23
Publication Date
2026-03-27

AI Technical Summary

Technical Problem

Traditional park monitoring systems rely on manual interpretation, resulting in low efficiency and a high false alarm rate. They cannot achieve proactive early warning and precise prevention and control, and the lack of coordination and linkage among various security subsystems leads to delayed response.

Method used

By deploying sensing devices to collect environmental data, using edge computing for lightweight target detection and multi-target tracking, and combining rule matching and a three-dimensional credibility fusion model, risk aggravation warning signals are generated, and device linkage and closed-loop management are achieved.

Benefits of technology

It has enabled a shift from post-event handling to in-event suppression and pre-event prevention, improving the reliability of alarm information and the efficiency of security response, and forming a self-learning and self-optimizing intelligent security ecosystem.

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Abstract

The invention discloses a method for monitoring and identifying dangerous behaviors of a smart park, and relates to the field of intelligent security and protection. The method comprises the following steps: acquiring an environment data stream through a sensing device deployed at a key point location of a park and carrying out standardization processing on the environment data stream; the data stream is sent to an edge computing node, a target is recognized through a lightweight target detection model, the detection confidence coefficient is obtained, a motion track is generated through a multi-target tracking algorithm, the rule matching degree is calculated according to a predefined rule base, and dangerous behaviors are preliminarily recognized; calculating a comprehensive model prediction credibility based on the detection credibility and the rule matching degree, and generating a final comprehensive credibility through a multi-dimensional credibility fusion model in combination with the time sequence consistency credibility and the scene matching credibility; and dangerous behavior trend prediction is carried out according to the comprehensive confidence, and an alarm instruction is generated to trigger disposal linkage, so that advanced prevention and quick response of dangerous behaviors are realized, and the intelligent level and operation and maintenance efficiency of park security and protection are greatly improved.
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