Agricultural problem prediction and decision support system based on large model

Through a large-scale agricultural problem prediction and decision support system, multi-source data is integrated and policy response is combined to generate accurate agricultural activity suggestions, solving the problem of inefficient production in traditional agriculture and achieving efficient and intelligent decision-making support for agricultural production.

CN120338416APending Publication Date: 2025-07-18TIANFU JIANGXI LAB
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Patent Information

Application Number
CN202510486533.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-04-18
Publication Date
2025-07-18

AI Technical Summary

Technical Problem

Traditional agricultural production relies on farmers' experience, is inefficient and is wasteful, and the existing technology lacks dynamic adaptability and cross-domain information integration, making it difficult to cope with changes in market and regulations. Agricultural AI solutions are sensitive to environmental changes and have poor adaptability.

Method used

A large-model-based agricultural problem prediction and decision support system is adopted, including data collection and preprocessing modules, agent large-model modules, policy response modules and decision support modules, integrated satellite images, meteorological data, soil data, etc., and dynamically adjust strategies for agricultural activities are generated in combination with the policy response module.

Benefits of technology

Improve agricultural production efficiency and accuracy, enhance adaptability to environmental changes, optimize resource allocation, support sustainable agricultural development, improve the intelligence level of decision-making support systems, reduce resource waste, simplify information acquisition processes, and enhance risk management and economic security.

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Abstract

The invention provides an agricultural problem prediction and decision support system based on a large model, and the system comprises a data collection and preprocessing module which is used for collecting data resources of a plurality of channels, and carrying out the data cleaning, data conversion and data storage through a distributed calculation framework; the intelligent agent large model module comprises a large model for agricultural problem prediction, and the large model is trained by adopting historical data; the policy response module is used for extracting information in the policy file, converting the information into structured data and providing a calling interface; and the decision support module is used for generating specific farming activity suggestions based on the structured data in the policy response module and the prediction result of the agent large model module. The system provided by the invention can dynamically provide suggestions in response to farming activities according to crop growth conditions.
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