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Visualization Research and Application of Water Quality Monitoring Data Based on ECharts

Yifu Sheng1, Weida Chen, Huan Wen1, Haijun Lin1, Jianjun Zhang1, *

1 College of Engineering and Design, Hunan Normal University, Changsha, China.
2 Zhaoyin Network Technology (Shenzhen) Co., Ltd., Shenzhen, China.

* Corresponding Author: Jianjun Zhang. Email: email.

Journal on Big Data 2020, 2(1), 1-8. https://doi.org/10.32604/jbd.2020.01001

Abstract

Water resources are one of the basic resources for human survival, and water protection has been becoming a major problem for countries around the world. However, most of the traditional water quality monitoring research work is still concerned with the collection of water quality indicators, and ignored the analysis of water quality monitoring data and its value. In this paper, by adopting Laravel and AdminTE framework, we introduced how to design and implement a water quality data visualization platform based on Baidu ECharts. Through the deployed water quality sensor, the collected water quality indicator data is transmitted to the big data processing platform that deployed on Tencent Cloud in real time through the 4G network. The collected monitoring data is analyzed, and the processing result is visualized by Baidu ECharts. The test results showed that the designed system could run well and will provide decision support for water resource protection.

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APA Style
Sheng, Y., Chen, W., Wen, H., Lin, H., Zhang, J. (2020). Visualization research and application of water quality monitoring data based on echarts. Journal on Big Data, 2(1), 1-8. https://doi.org/10.32604/jbd.2020.01001
Vancouver Style
Sheng Y, Chen W, Wen H, Lin H, Zhang J. Visualization research and application of water quality monitoring data based on echarts. J Big Data . 2020;2(1):1-8 https://doi.org/10.32604/jbd.2020.01001
IEEE Style
Y. Sheng, W. Chen, H. Wen, H. Lin, and J. Zhang "Visualization Research and Application of Water Quality Monitoring Data Based on ECharts," J. Big Data , vol. 2, no. 1, pp. 1-8. 2020. https://doi.org/10.32604/jbd.2020.01001

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cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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