A multi-dimensional greenhouse monitoring system and method based on the Internet of Things

By constructing a multi-dimensional state vector and coupling sensitivity, target control coefficients are generated, solving the problem of fragmented control caused by independent adjustment of various environmental variables in the greenhouse, realizing multi-variable collaborative optimization control, and improving the stability and consistency of the greenhouse environment.

CN121578847BActive Publication Date: 2026-07-21FUJIAN AGRI VOCATIONAL & TECH COLLEGE
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
FUJIAN AGRI VOCATIONAL & TECH COLLEGE
Filing Date
2026-01-28
Publication Date
2026-07-21

AI Technical Summary

Technical Problem

In existing greenhouse multivariate regulation technologies, the independent adjustment of each environmental variable leads to fragmented regulation and repeated adjustments, making it difficult to adapt to the dynamic needs of crops at different growth stages, and the overall environmental stability is insufficient.

Method used

By acquiring multi-source sensor data of the greenhouse environment, constructing a multi-dimensional state vector, extracting disturbance response characteristics and coupling sensitivity, generating target control coefficients, determining conflicts between variables, and identifying multi-variable joint control commands, the coordinated optimization control of environmental variables is achieved.

Benefits of technology

It reduced regulation deviations, improved the overall reliability and consistency of greenhouse environment regulation, avoided deviation expansion caused by inconsistent variable execution rhythms, and achieved stable relationships among multiple variables.

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Abstract

The application provides a multi-dimensional greenhouse monitoring system and method based on the Internet of Things. The multi-dimensional state vector of the greenhouse environment is determined by multi-source sensing data in the greenhouse environment. The disturbance response characteristics of the greenhouse environmental variables to crop growth are extracted from the multi-dimensional state vector. The coupling sensitivity of the greenhouse environmental variable regulation is generated based on the disturbance response characteristics. The multi-variable regulation deviation of the greenhouse in the current crop growth stage is determined according to the current multi-dimensional state vector of the greenhouse. Then, the target regulation coefficient of each environmental variable in the greenhouse is generated according to the regulation deviation. The regulation coupling relationship between different environmental variables in the greenhouse is determined by all target regulation coefficients. The multi-variable joint control instruction of the greenhouse environment regulation is determined by the regulation coupling relationship and the coupling sensitivity. Then, the multi-variable stable control of the environmental variables in the greenhouse is performed. By using the scheme, the multi-variable collaborative optimization control can be realized in the complex and variable greenhouse environment, so as to reduce the regulation deviation.
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