A fish behavior dynamic monitoring and data analysis method for a fish passage of a water conservancy project

By constructing a multimodal fusion fish behavior monitoring system, the problems of insufficient multimodal data fusion and coarse behavior recognition in fish behavior monitoring in water conservancy projects have been solved. This system achieves high-precision fish behavior monitoring and ecological event analysis, has adaptive and proactive early warning capabilities, and enhances scientific decision support for aquatic ecosystem management.

CN121542787BActive Publication Date: 2026-07-24POWER CHINA KUNMING ENG CORP LTD +2
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
POWER CHINA KUNMING ENG CORP LTD
Filing Date
2025-10-14
Publication Date
2026-07-24

AI Technical Summary

Technical Problem

Existing technologies for monitoring fish behavior in water conservancy projects suffer from several problems, including insufficient multimodal data fusion, coarse identification of individual and group behaviors, difficulty in achieving spatiotemporal continuity and efficient anomaly detection, and a lack of ecological causal mechanism modeling and intelligent feedback loop.

Method used

An integrated monitoring system is constructed that combines multi-source feature collaborative extraction, trajectory autonomous shaping, swarm intelligence aggregation, real-time early warning of behavioral anomalies, and in-depth ecological causal analysis. Through multimodal synchronous acquisition and preprocessing, fusion feature extraction, target aggregation and local behavior recognition, large-scale behavioral event recognition, and ecological causal modeling, a high-precision, full-process, and self-evolving intelligent monitoring and management of fish passage behavior is achieved.

Benefits of technology

It significantly improves the accuracy and timeliness of fish behavior event identification, possesses high versatility, strong adaptability and proactive early warning capabilities, can adaptively integrate multi-source data, accurately track the spatiotemporal dynamics of individual fish and groups, identify complex ecological events in real time, and combine environmental parameters to deeply analyze the ecological driving forces of behavior, providing reliable and efficient intelligent technical support.

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Abstract

A kind of water conservancy hub fish passage fish behavior dynamic monitoring and data analysis method belongs to the field of water conservancy hub fish population ecological monitoring. The method is by arranging multiple types of sensors at key nodes of the fish passage, realizing multi-modal synchronous fusion of video, sonar and environmental data based on global clock, and processing time alignment and spatial relocation of data;Using feature extraction and motion trajectory splicing, real-time continuous identification of fish targets and their behavior changes;Through behavior clustering and event interpretation, distinguish the micro behavior of fish individuals and groups and the large-scale behavior events in the passage, and model and analyze the causal relationship between fish behavior and environmental parameters by integrating neural causal tensor mapping. The system can dynamically warn and feedback abnormal behavior, and improve the intelligent level of water conservancy hub ecological protection and fish return passage management.
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