Design And Implementation Of River Pollution Source Filtering System Based On Location Service

Socio-economic development often sacrifice ecological environment as its cost.In recent years,sudden river water pollution accidents happened frequently,and have caused a bad environmental influence.At present,the relevant departments find the source of water pollution,locate the enterprises which suspected discharging pollutants in the upper reaches of the river and then send relevant personnel to visit and check,the entire process is in the stage of manual work,the process is too long,the efficiency is too low.How to scientifically and efficiently manage rivers and cope with sudden water pollution incidents from the source of pollution has become an urgent problem to be solved.Based on the river management actual needs and a large number of actual investigations,relying on information systems and information processing technologies,the river pollution source filter system based on location services is designed and implemented in this paper.The paper mainly focuses on the three aspects,which are the management of state key controlled heavy metal polluting enterprises along the rivers in Yunnan Province,locating and filtering after the occurrence of sudden water pollution,and water quality risk monitoring and early warning.The system adopts the B/S architecture and the Resin server,uses JavaScript and Java hybrid programming method to achieve an integrated management system that integrates river enterprise management and pollution location monitoring and early warning.The system mainly includes the system management module,the enterprise management module,the river management module,the pollution source positioning module,the pollution monitoring and the warning module.To solve the requirement of river pollutant content prediction,the neural network water quality prediction model based on genetic algorithm is proposed,the comparison of experimental simulation proves that the prediction model is effective.The establishment of theoretical algorithms and the system both achieve the pollution monitoring and early warning functions and can provide technical support for river pollution emergency warning.