Crop planting management system and method based on cloud services

Abstract

Embodiments of the invention provide a crop planting management system and method based on cloud services. The system comprises an information acquisition subsystem used for acquiring growth process data of target crops and environment data of a target crop planting area in real time, a data analysis service subsystem used for storing and processing the data acquired by the information acquisitionsubsystem and building a planting management decision model of the target crops based on deep learning, a visual subsystem used for performing growth period recognition, disease and pest recognition,growth vigor recognition, intrusion recognition and yield prediction on the target crops, a management service decision subsystem used for realizing seeding control, fertilization control, irrigationcontrol, environment control, production archive management, disease and pest control, intelligent equipment patrol and early warning, and a display pushing subsystem used for sending a decision result to an intelligent equipment terminal and a user terminal for displaying. The crop planting management system and method based on cloud services can be used for realizing intelligent, scientific andunmanned agricultural planting management.

Description

technical field [0001] The present invention relates to the technical field of agricultural intelligence, and more specifically, to a cloud service-based crop planting trusteeship system and method. Background technique [0002] With the progress of society, the degree of intensification of agricultural land has been further improved, more and more modern technical equipment has been applied in agriculture, and the level of agricultural water conservancy, mechanization and informatization has gradually improved, but crop planting management in the park is more Relying on human experience, lacking scientific basis and systematic management methods, and increasing labor costs and increasing energy consumption, the solution to these problems needs to rely more on intelligent management systems and methods. [0003] The existing intelligent devices for agricultural planting management include: water and fertilizer integration equipment and environmental control devices, crop pla...

AI Technical Summary

Problems solved by technology

[0004] At present, there are the following problems in the intelligent devices of agricultural planting management: 1) There is no mature management device or method for the whole growth period of crop planting in the current agricultural field, the existing irrigation and environmental control equipment are relatively independent, and the integration of water and fertilizer is mostly used for irrigation and fertilization Equipment and environmental management only monitor meteorological and moisture information, and do not combine environmental information and water and fertilizer management with crop growth requirements; 2) Existing water and fertilizer integrated equipment and environmental control devices still rely on extensive experience or regular quantitative The management mode lacks scientific basis and intelligent decision-making methods, and does not consider the factors affecting crop growth; 3) The cloud platform of crop planting devices on the market is only a data collection platform, which can realize remote control without data analysis and intelligent decision-making algorithms can only play an auxiliary role in production, and a large number of personnel are still required to participate in the production; 4) The crop planting intelligent devices on the market are highly specialized, and most of them are complicated to operate, requiring professional technicians to maintain them. In the absence of personnel, it is easy to cause idle waste of equipment

Therefore, most of the parks hire professional personnel with high salaries and need to invest a lot of money; 5) Equipment operation and maintenance, as a labor-intensive industry, is facing practical problems such as rising labor costs, insufficient funds, low operating efficiency and management efficiency

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