Ecological agriculture management and control method and system based on deep learning and image recognition technology

Through the ecological agricultural control system based on deep learning and image recognition technology, the problem of obtaining agricultural environment image data and segmenting target areas is solved, real-time monitoring and dynamic control of the agricultural environment are realized, and the accuracy of monitoring and efficiency of control are improved.

CN119693882AActive Publication Date: 2025-03-25SHAANXI INST OF BIOLOGICAL AGRI +1
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Patent Information

Application Number
CN202510208629.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-02-25
Publication Date
2025-03-25
Estimated Expiration
2045-02-25

AI Technical Summary

Technical Problem

The existing technology has failed to effectively solve the problem of how to obtain image data of the agricultural environment, segment the target area, extract, classify and analyze the target area, and judge whether there are abnormalities in the agricultural environment to dynamically adjust the management and control measures.

Method used

Provides an ecological agricultural management and control system based on deep learning and image recognition technology, including image acquisition module, feature classification module, analysis and early warning module and dynamic management and control module. The system obtains agricultural environment image data through drones, segments target areas, extracts features, classifies targets, and analyzes regional features to determine whether there are abnormalities in the agricultural environment and dynamically adjusts control measures.

Benefits of technology

Real-time, comprehensive and accurate monitoring of target areas in the agricultural environment is achieved, data accuracy is ensured, and efficient and accurate classification of different targets in the agricultural environment is improved, potential abnormalities or risks are discovered in a timely manner, control measures are dynamically adjusted, resource utilization efficiency is improved, and manual intervention is reduced.

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Abstract

The invention relates to the technical field of image recognition, and provides an ecological agriculture management and control method and system based on deep learning and an image recognition technology, and the method comprises the steps: obtaining the image data of an agricultural environment through an image obtaining module, segmenting a target region, and achieving the real-time, comprehensive and precise monitoring of the target region in the agricultural environment; the feature classification module performs feature extraction on the target region to obtain region features, and performs target classification according to the region features, so that efficient and accurate classification of different targets in an agricultural environment is realized, and accurate agricultural data support is provided; the analysis and early warning module analyzes the regional features, judges whether the agricultural environment is abnormal or not, and generates early warning information, so that intelligent analysis of the agricultural environment is realized, potential abnormity or risks can be found in time, early warning is given out, farm managers are helped to take measures in advance, and expansion of problems is prevented; and the dynamic management and control module dynamically adjusts management and control measures according to the early warning information and feeds back a management and control effect.
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