Method and system for monitoring fishery propagation and release operation based on cooperation of unmanned aerial vehicle cluster

CN121903795BActive Publication Date: 2026-06-05SOUTH CHINA SEA FISHERIES RES INST CHINESE ACAD OF FISHERY SCI
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
SOUTH CHINA SEA FISHERIES RES INST CHINESE ACAD OF FISHERY SCI
Filing Date
2026-03-20
Publication Date
2026-06-05

AI Technical Summary

Technical Problem

In existing fishery stock enhancement and release operations, the efficiency and scope of aquatic environment monitoring are low. Single drone monitoring cannot achieve simultaneous acquisition of multi-dimensional data, and traditional technologies lack multi-dimensional parameter analysis, resulting in unreasonable selection of release areas and unscientific setting of release quantities, which affects the ecological and economic benefits of stock enhancement and release.

Method used

The system employs a drone swarm collaborative working mode, using high-definition cameras and multispectral sensors to collect data, construct a multi-dimensional environmental index, introduce the Dijkstra algorithm to analyze the migration trend of water body fitness, and generate a release planning scheme.

Benefits of technology

It enables multi-dimensional synchronous monitoring of a large area of ​​water, improves the accuracy and reliability of monitoring data, accurately predicts the swimming and dispersal patterns of fish fry, and scientifically plans the release of fish fry, thereby improving the survival rate of fish fry and the efficiency of stock enhancement and release.

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Abstract

The application discloses a fishery propagation releasing operation monitoring method and system based on unmanned aerial vehicle cluster cooperation, and comprises the following steps: according to a target water area, a plurality of monitoring areas are divided, high-definition images and multispectral data of each area are acquired through unmanned aerial vehicle cluster cooperation, and blurred images are collected and corrected twice in cooperation; based on the high-definition images, a first environmental index is generated by analyzing water transparency and other indexes, and based on the multispectral data, a second environmental index is generated by analyzing chlorophyll and other parameters; an environmental evaluation is obtained by weighting the environmental index, and a multi-path migration area is determined, a Dijkstra algorithm is introduced to analyze the environmental moderate migration direction and migration index; according to the migration condition, the releasing quantity is set, and a releasing planning scheme is generated. The application solves the problems of low monitoring efficiency and one-sided evaluation of traditional technology, improves the scientific nature and efficiency of releasing, and is suitable for multi-water area scenes.
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Citation Information

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