Greenhouse environment tomato parameter intelligent monitoring system based on neural network
By integrating multi-source data and dynamically adjusting the weights of the intelligent monitoring system for greenhouse environmental parameters based on neural networks, the problems of single parameters and incomplete evaluation in traditional monitoring methods have been solved, thus achieving accurate assessment of the greenhouse environment and improving the growth quality of tomatoes.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- GANSU AGRI UNIV
- Filing Date
- 2026-06-12
- Publication Date
- 2026-07-17
AI Technical Summary
Traditional greenhouse monitoring methods rely on a single dimension of parameter acquisition, and multi-source data are easily affected by noise. The evaluation model cannot capture the nonlinear correlation between parameters and the dynamic changes in time series, resulting in incomplete and inaccurate evaluations.
A greenhouse environmental parameter intelligent monitoring system based on neural networks is adopted. Through data acquisition module, hierarchical health assessment system, weight calculation module, neural network evaluation module and multi-source information fusion module, combined with fuzzy hierarchical analysis method, entropy weight method and Bayes theory, multi-source data fusion and dynamic weight adjustment are carried out to adapt to the needs of tomatoes at different growth stages.
This has led to a comprehensive and accurate improvement in greenhouse environmental parameters, providing reliable data support and ensuring the improvement of tomato growth quality and yield.
Smart Images
Figure CN122413152A_ABST