Agricultural sensor crop precision nutrition system and method based on artificial intelligence

Abstract

The invention belongs to the technical field of intelligent agricultural management, and particularly relates to an agricultural sensor crop precision nutrition system and method based on artificial intelligence. The system comprises a central workstation, an intelligent user side and a cloud side system, the service range of the central workstation covers the whole agricultural planting area, agricultural sensors are adopted for collecting agricultural information, and agricultural services including but not limited to data transmission and nutrient supply are completed; the intelligent userside is used for displaying information, collecting abnormal seedling condition images and purchasing nutrition supply service; and the cloud system processes and analyzes the information. The invention provides an agricultural condition sampling means comprising multi-mode planting parameter acquisition and abnormal seedling condition image acquisition. In two stages of working processes providedby the system, an analysis object is reduced from a large-scale 'agricultural planting area' to a small-scale 'problem partition', so that the pertinence and accuracy of an agrochemical service scheme obtained by data analysis are gradually improved.

Description

Technical field [0001] The invention belongs to the technical field of intelligent agricultural management, and in particular relates to an artificial intelligence-based agricultural sensor crop precise nutrition system and method. Background technique [0002] The monitoring of planting environment and crop growth is an important part of the monitoring of agricultural conditions. Through real-time status monitoring and adjusting countermeasures and solving problems according to actual conditions, it is conducive to realize the precise supply of water, light and nutrients, improve agricultural production efficiency and quality of agricultural products, and promote the green development of traditional agriculture. [0003] As recorded in the Chinese invention patents with patent numbers CN201621183257 and CN201910253674 in the prior art, agricultural sensors are now widely used in the monitoring of planting environments and crop growth. In the existing technical solutions, a large ...

AI Technical Summary

Problems solved by technology

Standard data is likely to have limitations in terms of professionalism and accuracy, and cannot provide effective reference; secondly, in the existing crop monitoring technology, although there are technologies that use sensors for "zonal collection" and "independent analysis" of agricultural data However, in view of the extremely high complexity of agricultural production activities, multiple factors such as soil type, water content, organic matter content, and temperature will affect the measurement accuracy of agricultural sensors, making it difficult for the system to obtain information that truly reflects the planting area environment and crop growth conditions. Accurate values; in addition, compared with collecting data, the real growth status of crops is a more intuitive way to reflect whether the application of water, light and nutrients is reasonable

Therefore, it is difficult to guarantee the accuracy, rationality, and effectiveness of using sensor data only as a method to formulate agricultural operation plans such as irrigation, lighting, and nutrient supply.

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