Environment data-oriented remote control method for nitrogen and phosphorus loss amount of paddy field

By constructing a hybrid modeling architecture that combines a lightweight residual convolutional neural network and a mechanism-constrained sub-model, high-precision, interpretable, and low-latency dynamic prediction of nitrogen and phosphorus loss in paddy fields was achieved. This generated executable remote control commands, solving the problems of poor model interpretability and low computational efficiency in existing technologies, and reducing the risk of nitrogen and phosphorus loss in paddy fields.

CN121706032BActive Publication Date: 2026-05-01INST OF SOIL FERTILIZER & RESOURCE ENVIRONMENT JIANGXI ACAD OF AGRI SCI
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Patent Information

Application Number
CN202610209704.2
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2026-02-13
Publication Date
2026-05-01
Estimated Expiration
2046-02-13

AI Technical Summary

Technical Problem

In existing technologies, purely data-driven artificial intelligence models have poor interpretability and rely on a large amount of labeled data, while purely mechanistic models have complex parameters and low computational efficiency, making it difficult to support real-time remote control of nitrogen and phosphorus loss in paddy fields.

Method used

A hybrid modeling architecture integrating physical mechanism constraints and data-driven learning capabilities is constructed. By coupling a lightweight residual convolutional neural network and a mechanism constraint sub-model, predicted values ​​of nitrogen and phosphorus loss that conform to the law of conservation of matter are generated, and executable remote control commands are generated based on the predicted values.

Benefits of technology

It achieves high-precision, interpretable, and low-latency dynamic prediction of nitrogen and phosphorus loss in paddy fields, generates directly related and executable agricultural operation instructions, reduces the risk of nitrogen and phosphorus loss in paddy fields, and improves the level of intelligent control of agricultural non-point source pollution.

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Abstract

The present application relates to the field of agricultural environmental information technology, and discloses a remote control method for nitrogen and phosphorus loss amount of paddy field facing environmental data. The method comprises the following steps: obtaining historical nitrogen and phosphorus loss data, real-time meteorological data and water and fertilizer operation information of the paddy field; constructing a mechanism constraint sub-model combining nitrogen migration and transformation dynamics and phosphorus adsorption and desorption balance; performing multi-source feature extraction on the meteorological data to generate a standardized environmental vector; inputting the light residual convolutional neural network to output an initial prediction value; combining the mechanism model to generate a corrected prediction value conforming to the conservation of mass through the Lagrange multiplier method; when the prediction value exceeds the threshold value, generating a drainage gate opening degree and a fertilizer plan adjustment instruction, and delivering the instruction to an edge terminal for execution through a narrowband Internet of Things.
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