The Design And Implementation Of Data Plateform Of Monitoring And Early Warning For Tea

With the rapid development of technologies such as the Internet,the Internet of Things,and artificial intelligence,traditional agriculture is gradually moving toward modernization.In the era of modern agriculture,fundamental changes have taken place in agricultural monitoring and early warning.The objects it studies and analyzes have become more detailed.The Central Document No.1 for many years was related to agriculture,but it was still relatively backward in agricultural monitoring and earlywarning in the poverty-stricken mountainous regions where agriculture was the main focus.In terms of management and cultivation,it still followed the practice of relying on traditional experience.In the Enshi Tujia and Miao Autonomous Prefecture,the local tea industry with poverty alleviation is in the above-mentioned backward state.In this context,we urgently need to build a modern monitoring and early-warning data platform for the local area to promote the modernization of agriculture in ethnic minority areas.This paper uses single-chip technology and various sensors to collect agricultural data,uses machine learning technology to build intelligent analysis model,and finally builds a visual tea monitoring and early-warning data platform based on front-end and back-end separation and development technologies.From the specific implementation point of view,tea monitoring and early warning data platform is mainly divided into three working links: data acquisition,data processing and data applications.The main work of this paper is centered on these three links.The specific work includes: 1)Data acquisition: The platform uses various sensors to collect environmental data of tea planting bases,and uses the Arduino processor for preliminary processing and transmission;2)Data processing : For various types of environmental data collected,on the one hand,linear regression models are trained based on machine learning methods to obtain applicable early warning models.On the other hand,database design is based on MySQL database,and APIs are developed based on front-end and back-end separated development models.Interface development,for the data application link to do the basics;3)data applications: The platform uses the web front end and Echarts related technologies to complete the specific implementation of the platform,built a set of early warning release,real-time monitoring and environmental data visualization in one platform.The main features of this platform are: 1)Accurate and extensive data monitoring: The platform is equipped with sensors at the tea base to be able to monitor the data closely related to tea planting bases and accurately correspond to each base and company.The collected data is in addition to the traditional weather environment data,as well as PM2.5,soil moisture,and other data;2)Complete monitoring and early warning of all aspects: At present,many research and molding platforms focus on data acquisition,processing,and application.One or two rings in the link,and the workflow of this platform runs through three links,completing a full set of tea monitoring and early warning work;3)It is easy to expand and modify: This platform is based on the B/S architecture and the front-end and back-end separation development model.To carry out development,the work corresponding to each of the three links can be independently developed,and any changes in the future will have little impact on other links.