Design And Implementation Of Pollution Data Acquisition System Based On Industrial Monitoring Software

With the rapid economy development since the starting of Reform and Open policy,environment pollution is getting worse and worse, which risk people’s lives and properties,and damage the nature itself. Environment protection, including monitoring environmentpollution sources and forecasting pollution, becomes more and more urgent. Therefore, byintegrating the latest computer network technologies, and configuration software technologies,in this thesis, we have developed an environment monitoring system which can fetch datafrom remote monitoring devices, and forecast pollution based on the received data, so thatenvironment department can ameliorate pollution sources in advance which reduce the costfor environment protection significantly.In the thesis, we firstly introduce the architecture of environment monitoring system, andthe technologies of configuration software and the remote monitoring device eNet. Secondly,we realize a kingView’s driver which enables kingView to communicate with remote eNet, soas to fetch data from eNet. Based on the received data, we devise an improved EvolutionaryNeural Network algorithm to predict the future pollution.The experiments on the system show that the system can robustly and accurately receivedata from remote monitoring device. By comparing to the existing trend forecasting methods,our improved Evolutionary Neural Network algorithm shows more efficient performance inforecasting. Our better forecasting results will provide more reliable support to environmentdepartment to ameliorate pollutions.