Analysis and decision support strategy based on agricultural big data

By establishing an agricultural big data platform, integrating multi-source data and adopting advanced machine learning algorithms and edge computing technologies, the problems of low data utilization efficiency and insufficient decision support in modern agriculture are solved, and the precise and intelligent management of agricultural production is achieved.

CN119940971APending Publication Date: 2025-05-06SPACE VISION (CHONGQING) TECH CO LTD
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Patent Information

Application Number
CN202510068167.X
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-01-16
Publication Date
2025-05-06

AI Technical Summary

Technical Problem

In modern agriculture, data utilization efficiency is low and decision-making support is insufficient. It is difficult for existing systems to integrate multi-source data, provide real-time and accurate decision-making support, adopt advanced machine learning algorithms, and poor scalability.

Method used

By establishing an agricultural big data platform, integrating multi-source data, and adopting advanced machine learning algorithms and edge computing technology, multi-dimensional decision support is provided to enhance the scalability and maintainability of the system.

Benefits of technology

It realizes the accurate and intelligent management of agricultural production, improves the real-time and accuracy of data utilization efficiency and decision-making support, and meets the needs of modern agriculture for high-precision and intelligent management.

✦ Generated by Eureka AI based on patent content.

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Abstract

The invention provides an analysis and decision support strategy based on agricultural big data, and innovatively provides a double-layer architecture of'edge computing + semantic network 'for the problems of scattered agricultural data and poor real-time performance in the prior art. The RDF Schema semantic network technology is applied to agricultural multi-source data fusion, and deep correlation analysis of equipment data of sensors, meteorological stations, soil monitoring and the like is achieved. On the basis of an edge calculation distributed real-time processing framework, a Bayesian optimization image enhancement algorithm is combined, and the disease and pest detection accuracy is remarkably improved. A'data analysis-knowledge reasoning-intelligent decision 'three-layer progressive platform is autonomously designed, farming activities such as planting, fertilization, irrigation and the like are deeply integrated with an expert system, and precise decision support is realized. The multi-source heterogeneous data semantic fusion method has three innovation breakthroughs: firstly, multi-source heterogeneous data semantic fusion is realized; 2, constructing an edge calculation driving real-time processing system; and thirdly, an intelligent progressive decision-making platform is established, and the method has remarkable advantages in the aspects of data fusion efficiency and decision-making accuracy.
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Citation Information

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