A multi-modal fusion regional intrusion detection and early warning method and system

By employing a multimodal fusion-based regional intrusion detection method, utilizing a sensor array of cameras, thermal imaging, and radar sensors, and combining hierarchical feature fusion and semantic alignment strategies, the problem of high false alarm rate and insufficient response in traditional systems is solved, achieving highly accurate and intelligent intrusion detection and early warning.

CN122116536APending Publication Date: 2026-05-29CHAINT CORP
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
CHAINT CORP
Filing Date
2026-04-01
Publication Date
2026-05-29

AI Technical Summary

Technical Problem

Traditional area intrusion detection systems rely on a single sensor, are susceptible to environmental interference, have a high false alarm rate, and lack fine-grained response capabilities, making it impossible to differentiate intrusion behavior.

Method used

A multimodal fusion-based regional intrusion detection method is adopted. Through a sensor array composed of cameras, thermal imaging sensors and radar sensors, combined with hierarchical feature fusion and semantic alignment strategies, a multimodal model is used to determine intrusion and generate natural language descriptions to achieve differentiated linkage of devices.

Benefits of technology

It significantly improves the accuracy and robustness of intrusion detection, reduces the false alarm rate, enables a deeper understanding and accurate judgment of intrusion behavior, and enhances the system's intelligent decision-making level and the timeliness of device linkage.

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Abstract

The present application relates to the technical field of intelligent security and protection, and particularly relates to a multi-modal fusion regional intrusion detection and early warning method and system, the method collects multi-modal data through a sensor array, extracts features from the multi-modal data, and obtains joint representation by using a hierarchical feature fusion and semantic alignment strategy; frames the video data to obtain an alarm image set; inputs the joint representation and the alarm image set into a pre-trained multi-modal model to output an intrusion determination result and a target type; if it is determined that there is regional intrusion, a control instruction is generated based on the target type, and the control instruction is sent to security and protection equipment for security and protection equipment linkage. The present application method significantly improves the accuracy and environmental adaptability of intrusion detection through multi-modal sensor fusion and large model reasoning, and realizes intelligent security and protection equipment linkage control.
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