Crop assisting method, system and equipment based on multi-source remote sensing data and medium

By identifying crop varieties and growth stages through multi-source remote sensing data and combining it with genetic algorithms to optimize irrigation sequences, we solved the problems of traditional irrigation systems being unable to distinguish crop water requirements and low manual monitoring efficiency. This enabled accurate calculation and dynamic monitoring of crop water requirements, and improved monitoring frequency and irrigation efficiency.

CN120753178APending Publication Date: 2025-10-10INSPUR SMART TECH INNOVATION (SHANDONG) CO LTD
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Patent Information

Application Number
CN202510883227.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-06-28
Publication Date
2025-10-10

AI Technical Summary

Technical Problem

Traditional irrigation systems are unable to distinguish the water requirements of different crops, resulting in waste of water resources. Manual field surveys of crop types are inefficient and difficult to meet large-scale dynamic monitoring needs.

Method used

A method based on multi-source remote sensing data is adopted, using drones, satellite images and user terminals to identify crop varieties and growth stages, combined with genetic algorithms to optimize irrigation sequences, and the operation of irrigation devices is controlled by PID algorithms to achieve accurate calculation and dynamic monitoring of crop water requirements.

Benefits of technology

The accuracy of crop type prediction has been improved, and the monitoring frequency has been increased from monthly to daily, which reduces water waste, improves the timeliness and efficiency of irrigation, supports differentiated control of multiple irrigation devices, and eliminates unevenness caused by pipeline pressure fluctuations.

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Abstract

The invention discloses a crop assistance method, system and equipment based on multi-source remote sensing data and a medium, mainly relates to the technical field of crop assistance, and is used for solving the problem that water resources are wasted due to the fact that a traditional irrigation system cannot distinguish water demand characteristics of different crops. The manual field crop type investigation efficiency is low, and the large-range dynamic monitoring requirement is difficult to meet. Comprising the steps of determining crop varieties and growth stages of each preset area based on an unmanned aerial vehicle, a satellite image and a user terminal; obtaining a reference evapotranspiration value and a soil moisture variation, and obtaining the actual water demand of crops in the preset area according to the crop variety, the growth stage, the soil moisture variation and the reference evapotranspiration value; based on the initial irrigation sequence of the preset area and the fitness function, utilizing a genetic algorithm to obtain an optimized irrigation sequence; and based on the optimized irrigation sequence and the actual water demand of the crops, controlling the operation of the irrigation devices in the preset areas.
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