Intelligent irrigation control system based on BP neural network model

Abstract

In order to solve the problems of relatively backward agricultural irrigation technology, low utilization rate of water resources and serious waste, with raspberry pie as the main control chip, combined with all kinds of intelligent sensors, solenoid valve external control equipment, big data analysis and intelligent algorithm, an intelligent water-saving irrigation control system based on BP neural network is designed. The system takes raspberry pie as the main control module, according to the real-time weather forecast data of the current area obtained through WI-FI, and combined with the real-time monitoring of soil moisture by the soil moisture information collection module, the BP neural network model is used to intelligently judge whether irrigation is needed and automatically output the amount of water needed for irrigation. The test results of the system show that the predicted value of crop water demand based on BP neural network almost coincides with the expected value, indicating that the system can effectively and accurately predict crop water demand, and all kinds of modules controlled by raspberry pie can be combined organically, and the system is easy to operate, stable and reliable, and can provide optimal precision irrigation for crops. The system ensures the best growth of crops with the minimum amount of irrigation water, provides targeting and refinement for modern agriculture, effectively improves the utilization rate of water resources, has strong practicability, and has strong application value in agricultural production.