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Design and Analysis of a Water Quality Monitoring Data Service Platform 被引量:2

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摘要 Water is one of the basic resources for human survival.Water pollution monitoring and protection have been becoming a major problem for many countries all over the world.Most traditional water quality monitoring systems,however,generally focus only on water quality data collection,ignoring data analysis and data mining.In addition,some dirty data and data loss may occur due to power failures or transmission failures,further affecting data analysis and its application.In order to meet these needs,by using Internet of things,cloud computing,and big data technologies,we designed and implemented a water quality monitoring data intelligent service platform in C#and PHP language.The platform includes monitoring point addition,monitoring point map labeling,monitoring data uploading,monitoring data processing,early warning of exceeding the standard of monitoring indicators,and other functions modules.Using this platform,we can realize the automatic collection of water quality monitoring data,data cleaning,data analysis,intelligent early warning and early warning information push,and other functions.For better security and convenience,we deployed the system in the Tencent Cloud and tested it.The testing results showed that the data analysis platform could run well and will provide decision support for water resource protection.
出处 《Computers, Materials & Continua》 SCIE EI 2021年第1期389-405,共17页 计算机、材料和连续体(英文)
基金 the National Natural Science Foundation of China(No.61304208) Scientific Research Fund of Hunan Province Education Department(18C0003) Researchproject on teaching reform in colleges and universities of Hunan Province Education Department(20190147) Changsha City Science and Technology Plan Program(K1501013-11) Hunan NormalUniversity University-Industry Cooperation.This work is implemented at the 2011 Collaborative Innovation Center for Development and Utilization of Finance and Economics Big Data Property Universities of Hunan Province Open project grant number 20181901CRP04.
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