Design Of Smart Environment-Protecting Cloud And Big Data Analysis

Modern city gives rise to several problems and challenges,such as air pollution,noise pollution,water pollution,traffic jam,etc.While the computer technology and sensor technology are growing mature in recent years,the solution to these problems come into reality.The solution,called Smart City,is a method which makes use of computer technology,sensor technology,data mining technology and finally finds out what the problems are and how the problems can be solved.Environment-protection is one of the major projects related to peoples' well-being in our country,and it's also the focus of research and investment in our country.Environment-protection problem is one of the most important problems in Smart City.Therefore,we try to find out how to implement smart environment-protection by means of computer science.Our work uses different kinds of technologies in computer science to provide solutions to the problems.The solutions can be monitoring,evidence taking,managing,analyzing and predicting.Our work focuses on Smart Environment-protection from two aspects.First,we design and implement a Smart Environment-protection Cloud platform.Second,we do some big data analysis on several problems in Smart Environment-protection problems.Smart Environment-protection Cloud is a platform,aiming to sense and store environment-related data,and provide data visualization for users.Smart Environment-protection Cloud makes use of several techniques such as MongoDB,MySQL,Kafka,Netty,to build a platform,which is able to deal with several challenges in Smart Environment-protection such as huge amounts of data,changeable data types,high throughput demand of message passing,and large number of connections of monitoring devices.Smart Environment-protection Cloud provides data visualization by means of Web and iOS APP,and also provides related functions such as management and operations.Our work on big data analysis in Smart Environment-protection Cloud,mainly focuses on spatial prediction of air quality,temporal prediction of air quality and the relationship between management and data.In spatial prediction of air quality,our work combines data from Governmentmonitoring stations and Pollution-source stations to predict the air quality of an unmonitored area.The precision is 0.596.Our work in spatial prediction implied that our prediction method makes some sense,and also implies that data in Smart Environment-protection Cloud has huge value,since it can help find out the air pollution.Our work on temporal prediction of air quality,uses air quality data and other data of past several minutes,to predict the future air quality.The precision of our prediction is 0.703.The results show that our work can be used to predict.Our work on the relationship between management and data,proves that with the monitoring and management in Smart Environment-protection Cloud,the environment can be improved after some measures are taken.