Water contamination monitoring system based on big data: a case study Online publication date: Thu, 29-Aug-2019
by Gaofeng Zhang; Yingnan Yan; Yunsheng Tian; Yang Liu; Yan Li; Qingguo Zhou; Rui Zhou; Kuan-Ching Li
International Journal of Computational Science and Engineering (IJCSE), Vol. 19, No. 4, 2019
Abstract: Water plays a vital role in people's life, and individuals cannot survive without it. However, water contamination has become a serious issue with the development of industry and agriculture, and has become a threat to people's daily life. Moreover, the amount of data people need to process becomes excessively complex and huge in big data era. Hence, data management is increasingly a difficult task. There is an urgent need to develop a system to identify major changes of water quality through monitoring and managing these water quality variables. In this paper, we develop a data monitoring system named monitoring and managing data centre (MMDC) for monitoring, downloading, sharing, and time-series analysis based on big data technology. In order to reflect the real hydrological ecosystem, water quality variable data collected from Taihu Lake in China is used to verify the effectiveness of MMDC. Results show that MMDC brings effectiveness for monitoring and management of massive data. Although this investigation is focused on Taihu Lake, it is applicable as a general monitoring system for other similar natural resources.
Online publication date: Thu, 29-Aug-2019
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