Design And Research Of Variable Fertilization Control System Based On Cloud Computing

In order to improve the management level of variable rate fertilization,the control system of variable rate fertilization should be discussed and analyzed deeply.Through the literature review and study,it is found that there are still some problems such as too much redundancy,difficult to form data resources and isolation between systems.Therefore,under the background of the continuous development of the technology of the Internet of Things in agriculture,in order to realize the whole cloud management process from real-time collection of crop-related data to fertilization decision-making and then to fertilization control,this thesis studies and designs a variable rate fertilization control system based on cloud computing in detail,and the main research results are as follows:(1)The overall structure of variable rate fertilization control system is designed using cloud computing technology.This research follows the design ideas of hierarchy,objectification,parallelization and data service,designs the overall architecture of the variable rate fertilization control system based on cloud computing technology,and describes the key technologies involved in the system design in detail,so that the system has stable and reliable data transmission and simple and efficient management capabilities,and expands the application scope of cloud computing,It provides a new idea for intelligent fertilization management.(2)The construction of variable rate fertilization control device is proposed for cloud computing technology.After the analysis of the technical and functional requirements of the system,a set of variable rate fertilizer control device is designed with the single chip computer as the control core,combined with cloud computing and Internet of Things and other technologies,which mainly includes the hardware selection of the main control and irrigation parts and the design of remote data transmission protocol,and finally realizes the intelligent control and accurate management of the cotton field water and fertilizer supply.(3)The group intelligent control algorithm is studied and improved to optimize the control system of variable fertilization.In view of some problems existing in the fertilization process,the standard particle swarm optimization(PSO)algorithm and the gray wolf algorithm(GWO)are studied and improved,and the improved algorithms are DNPSO and GGWO respectively.Finally,the flow accuracy and stability of the system are verified by simulating and analyzing the system with MATLAB.The results show that compared with DNPSO control algorithm,GGWO-PID control system has better performance indexes,and can effectively improve the anti-interference and adaptive ability.(4)The cloud platform of drip irrigation intelligent variable fertilization service was built and tested.In order to implement the integration and application of the system,based on the analysis of the platform objectives,functions and performance requirements,the overall structure of the platform,data storage and core functional modules were designed,and the performance and function tests were completed.The results show that the design of the cloud platform meets the user’s needs for practicality,reliability and stability,and realizes the cloud management of the whole process from obtaining cotton nutrient information to topdressing decision-making to fertilization control based on cloud computing.To sum up,based on the overall planning of agricultural irrigation and fertilization,this research is based on the overall structure of the variable rate fertilization control system based on cloud computing,with the variable rate fertilization control device as the core,the swarm intelligent optimization algorithm as the auxiliary,and the fertilizer cloud platform as the support,ensuring the stability and integrity of the entire system structure.The experimental results show that the design of the system can improve the perception ability of cotton field information,the efficient transmission ability of data and the efficient implementation ability of fertilizer management,and improve the yield and economic benefits of crops under the condition of reducing production costs,making the research forward-looking.