基于Web技术的空气污染预警系统的研究
发布时间：2018-09-19 17:15
【摘要】：近几年环境污染问题越来越严重,其中大气污染问题尤为突出,大气污染严重影响了我们的健康生活,虽然相关部门已经实施了很多措施控制污染物的排放,但是到口前为止一直没有效的措施能够遏止污染的蔓延,大气污染仍是威胁我们健康的难题,在治理过程中,对污染物排放的监测预测必不可少。当今社会是一个物联网和互联网的时代,利用探测传感器再结合Web网络技术对污染物的排放进行实时监控是环保工作的发展趋势。本文所设计的监测预测系统的主要特点在于:1、服务器端利用Socket网络编程技术与下位机进行数据交互对其进行数据接收以及远程控制;2、系统通过JAVA开发并利用MySQL数据库对数据进行存储,主要利用Ajax技术进行Web系统前后台的数据交互;3、通过通过对大气污染物扩散模型的研究分析之后提出了融入风速、风向、雨量以及大气稳定度等影响因素的改进版高斯扩散模型,并且利用最小二乘法分析大量实验数据总结出误差补偿算法;4、利用百度地图的BMap技术结合预测模型分析出PM2.5的扩散分布图,以不同色块标识PM2.5的不同浓度值;5、利用了 Web技术对采集的数据实现了实时数据显示、历史数据管理、用户管理、远程设备管理、预警管理以及PM2.5扩散预测等功能。系统完成建立之后对无锡市一工厂的污染排放情况进行实地监测,总共设置了 10个长期监测站,在2016年6月至2016年12月采集了六个多月的数据,通过数据对比分析对预测模型进行了验证,分析结果表明预测值经过误差补偿后得到的PM2.5浓度值与实测值很接近,并且系统能够合理的预测在风速风向以及大气稳定度发生变化的情况下PM2.5的扩散情况,说明系统能够合理的对小尺度范围的污染情况进行实时监测以及对污染物扩散进行有效预测。整个系统的运行结果表明系统可以为有关环保部门的工作及居民的健康出现提供有效的数据支持。
[Abstract]:In recent years, the problem of environmental pollution has become more and more serious, especially the problem of air pollution, which has seriously affected our healthy lives, although the relevant departments have implemented many measures to control the discharge of pollutants. However, there are no effective measures to stop the spread of pollution. Air pollution is still a difficult problem that threatens our health. In the process of control, monitoring and forecasting of pollutant discharge is essential. Nowadays, the society is an era of Internet of things and Internet. It is the development trend of environmental protection work to use detection sensors and Web network technology to monitor the emission of pollutants in real time. The main features of the monitoring and forecasting system designed in this paper are: 1, the server uses Socket network programming technology to interact with the lower computer for data receiving and remote control. The system is developed through JAVA and uses MySQL number. The database stores the data, This paper mainly uses Ajax technology to carry out the data exchange between the front and back of Web system. After studying and analyzing the air pollutant diffusion model, the author puts forward the integration of wind speed and wind direction. An improved Gao Si diffusion model for factors such as rainfall and atmospheric stability, The error compensation algorithm is summed up by using the least square method to analyze a large number of experimental data, and the diffusion distribution map of PM2.5 is analyzed by using the BMap technology of Baidu map combined with the prediction model. Using different color blocks to identify the different concentrations of PM2.5, the functions of real-time data display, historical data management, user management, remote equipment management, early warning management and PM2.5 diffusion prediction are realized by using Web technology. After the establishment of the system, on-site monitoring of pollution emissions from a factory in Wuxi was carried out, with a total of 10 long-term monitoring stations and data collected from June 2016 to December 2016 for more than six months. The prediction model is verified by data comparison and analysis. The results show that the PM2.5 concentration obtained by error compensation is very close to the measured value. And the system can reasonably predict the diffusion of PM2.5 when wind speed and wind direction and atmospheric stability change. The results show that the system can monitor the pollution in a small scale in real time and predict the pollutant diffusion effectively. The operation results of the whole system show that the system can provide effective data support for the work of environmental protection departments and the emergence of residents' health.
【学位授予单位】：南京信息工程大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：X51;X84;TP393.09
本文编号：2250789
[Abstract]:In recent years, the problem of environmental pollution has become more and more serious, especially the problem of air pollution, which has seriously affected our healthy lives, although the relevant departments have implemented many measures to control the discharge of pollutants. However, there are no effective measures to stop the spread of pollution. Air pollution is still a difficult problem that threatens our health. In the process of control, monitoring and forecasting of pollutant discharge is essential. Nowadays, the society is an era of Internet of things and Internet. It is the development trend of environmental protection work to use detection sensors and Web network technology to monitor the emission of pollutants in real time. The main features of the monitoring and forecasting system designed in this paper are: 1, the server uses Socket network programming technology to interact with the lower computer for data receiving and remote control. The system is developed through JAVA and uses MySQL number. The database stores the data, This paper mainly uses Ajax technology to carry out the data exchange between the front and back of Web system. After studying and analyzing the air pollutant diffusion model, the author puts forward the integration of wind speed and wind direction. An improved Gao Si diffusion model for factors such as rainfall and atmospheric stability, The error compensation algorithm is summed up by using the least square method to analyze a large number of experimental data, and the diffusion distribution map of PM2.5 is analyzed by using the BMap technology of Baidu map combined with the prediction model. Using different color blocks to identify the different concentrations of PM2.5, the functions of real-time data display, historical data management, user management, remote equipment management, early warning management and PM2.5 diffusion prediction are realized by using Web technology. After the establishment of the system, on-site monitoring of pollution emissions from a factory in Wuxi was carried out, with a total of 10 long-term monitoring stations and data collected from June 2016 to December 2016 for more than six months. The prediction model is verified by data comparison and analysis. The results show that the PM2.5 concentration obtained by error compensation is very close to the measured value. And the system can reasonably predict the diffusion of PM2.5 when wind speed and wind direction and atmospheric stability change. The results show that the system can monitor the pollution in a small scale in real time and predict the pollutant diffusion effectively. The operation results of the whole system show that the system can provide effective data support for the work of environmental protection departments and the emergence of residents' health.
【学位授予单位】：南京信息工程大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：X51;X84;TP393.09
【参考文献】
相关期刊论文 前10条
1 肖凡;马娅婕;余ng;万勇;;Arduino和乐联网在PM2.5实时监测系统中的应用[J];自动化仪表;2015年12期
2 李祥余;;大气稳定度分类方法及判据比较研究[J];环境与可持续发展;2015年06期
3 陈静锋;柴瑞瑞;闫浩;夏继敏;刘德海;;基于高斯烟羽模型的PM2.5污染源扩散规律模拟分析[J];系统工程;2015年09期
4 任小强;陈金鹰;李文彬;胡波;;网络通信之Java Socket多线程通信[J];信息通信;2015年06期
5 王敏;黄滢;;中国的环境污染与经济增长[J];经济学(季刊);2015年02期
6 孙光明;王硕;;基于JSON的Ajax数据通信快速算法[J];计算机应用与软件;2015年01期
7 魏薇;傅丽芳;;基于改进高斯模型的哈尔滨市PM_(2.5)扩散问题实证分析[J];数学的实践与认识;2014年22期
8 陈甫;;Bootstrap3在Java Web项目中的应用[J];电脑编程技巧与维护;2014年17期
9 陈军;高岩;张烨培;杨阳;刘璧婷;;PM2.5扩散模型及预测研究[J];数学的实践与认识;2014年15期
10 王文博;赵培陆;梅笑冬;王彪;卢革宇;;基于Zig Bee的无线传感器网络大气监测系统设计[J];传感器与微系统;2014年02期
相关会议论文 前1条
1 陈杰;蒋文举;;突发性大气污染事故预警系统研究[A];成都市科技年会分会场——世界现代田园城市空气环境污染防治学术交流会论文集[C];2010年
相关硕士学位论文 前1条
1 易加仁;基于Web GIS的大气环境分析预测系统研究[D];武汉科技大学;2015年
，本文编号：2250789
本文链接：https://www.wllwen.com/guanlilunwen/ydhl/2250789.html
