Title: FSVA-data: a flexible solution for the visualisation and analysis of basin-scale water quality monitoring data

Authors: Jianlong Xu; Yuhui Li; Kun Wang; Lianghong Xiao; Wei Liang; Hongbo Zhou

Addresses: Colleage of Engineering, Shantou University, Shantou, China ' Colleage of Engineering, Shantou University, Shantou, China ' Colleage of Engineering, Shantou University, Shantou, China ' Shantou Environmental Protection Monitoring Station, Shantou, China ' College of Computer Science and Electronic Engineering, Hunan University, Changsha, China ' School of Software, Quanzhou University of Information Engineering, China

Abstract: Basin-scale water quality monitoring is an important part of water environment governance. However, owing to the multiple attributes, frequencies, methods, and data volume of water quality monitoring data, the efficient access, visualisation, and analysis of monitoring data is an important research topic in monitoring work. This paper proposes a flexible data visualisation and analysis solution, FSVA-data. In this solution, various microservices-based methods are used for integrated data discovery, processing, and analysis. To monitor data series that only change gently, we propose a data-adaptive method for data scalability and a customisable chart visualisation system. Our solution is not only used for water quality monitoring in Lianjiang River, but also has great application prospects in improving the effectiveness of monitoring data systems and accelerating scientific insights in other agricultural and ecological fields.

Keywords: visualisation; water quality monitoring; microservices.

DOI: 10.1504/IJES.2021.117941

International Journal of Embedded Systems, 2021 Vol.14 No.4, pp.335 - 344

Received: 27 May 2020
Accepted: 09 Jun 2020
Published online: 05 Oct 2021 *

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