Design And Implementation Of Air Quality Monitoring And Early Warning System Based On Microservice Architecture

Over the years,the worsening impact of air pollution has even seriously restricted the sustainable development of the social economy and has become a global problem.The process of industrialization and urbanization in my country,especially the early exploration of modernization,not only contributed to social and economic development,but also objectively aggravated air pollution.The good news is that the concepts and actions of green development and environmental protection priority have significantly changed the orientation of sacrificing the environment for development.Under the conditions of informatization,it seems promising and imperative to explore intensive,efficient,convenient and practical information technology means to better serve air pollution control in order to fundamentally reverse the situation of air pollution.This article takes Xi’an as an example,based on the air quality monitoring and early warning visualization system developed by the Weibo architecture.Under the premise of ensuring system reliability and scalability,real-time collection and monitoring of atmospheric environment monitoring data including PM2.5,PM10,SO2,CO2,CO,NO2,O3 and other evaluation indicators,and effective grasp of targets based on analysis models The status quo and evolution trend of urban air quality provide effective information and technical support for government management departments to help reduce pollution and reduce emissions,economic transformation,and healthy development.The specific research content and results are as follows:(1)architecture design.Learn and master the theory and technology related to microservices,follow the principle of splitting,apply Spring Cloud technology,and design a multi-module microservice architecture on the basis of realizing the splitting of single applications.In order to achieve high cohesion and low coupling performance of the system.(2)System implementation.Research and collect the air pollution indicator data of the Xi’an open source website,and use Python+Selenium crawler technology to save the data into the system database through the program.Through demand analysis,a variety of data visualization technologies are used to realize the main business function modules of the system,including user login and management microservices,real-time air quality monitoring and analysis microservices,historical data analysis and download microservices,early warning analysis microservices,etc.Finally,a log management module is added to monitor and manage the operation of the system in real time.Through functional testing and performance testing of the system,the system can meet the needs of real-time monitoring,historical data analysis and early warning,and can maintain a stable state under high concurrency and abnormal conditions.(3)Model application.Research and master the theory of neural network models,and verify and train the LSTM model in order to predict the accuracy of the results.Finally,based on the LSTM model,the air quality index is predicted,and the system early warning display function is realized.