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Smart Water Quality Monitoring System Design and KPIs Analysis: Case Sites of Fiji Surface Water

Author

Listed:
  • K. A. Mamun

    (School of Engineering and Physics, The University of the South Pacific, Suva, Fiji)

  • F. R. Islam

    (School of Science and Engineering, University of the Sunshine Coast, Queensland 4556, Australia)

  • R. Haque

    (School of Science and Engineering, University of the Sunshine Coast, Queensland 4556, Australia)

  • M. G. M. Khan

    (School of Computing, Information and Mathematical Sciences, The University of the South Pacific, Suva, Fiji)

  • A. N. Prasad

    (School of Engineering and Physics, The University of the South Pacific, Suva, Fiji)

  • H. Haqva

    (School of Engineering and Physics, The University of the South Pacific, Suva, Fiji)

  • R. R. Mudliar

    (School of Engineering and Physics, The University of the South Pacific, Suva, Fiji)

  • F. S. Mani

    (School of Biological and Chemical Sciences, The University of the South Pacific, Suva, Fiji)

Abstract

Over recent years, waters in and around Fiji has increasingly succumbed to a reasonable level of contamination. Water quality is defined with set of standards that clearly state the parameters of different properties in water. These standards are different at various geographic locations. The specific quantitative values of these parameters for the Fiji Islands are established by the Fiji National Drinking Water Quality Standards (FNDWQS). Fiji is geographically located in the vast Pacific Ocean, and requires a data collection framework for different water parameters to monitor water quality. The GIS framework system can effectively solve this continuously in real-time. With the end goal being to quantify different parameters; four (04) key performance indicators (KPI) are identified: Temperature, potential of hydrogen (pH), Oxidation Reduction Potential (ORP), and Conductivity. This paper presents a Smart Water Quality Monitoring System (SWQMS) which has been developed and deployed in five (05) Fijian locations (nodes) for the aforementioned KPIs measurement. The SWQMS interfaced with GIS and were powered using solar based Renewable Energy Source (REs). Finally, obtained data were tested and analyzed using statistical methods and verified comparing with the FNDWQS. The findings demonstrated that the system is capable of delivering an accurate and consistent measurement of water quality in real-time. Hence SWQMS could be a smart choice for various Pacific Island Countries (PICs) to use to monitor the water quality and in turn develop sustainable cities and societies.

Suggested Citation

  • K. A. Mamun & F. R. Islam & R. Haque & M. G. M. Khan & A. N. Prasad & H. Haqva & R. R. Mudliar & F. S. Mani, 2019. "Smart Water Quality Monitoring System Design and KPIs Analysis: Case Sites of Fiji Surface Water," Sustainability, MDPI, vol. 11(24), pages 1-21, December.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:24:p:7110-:d:296883
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    Citations

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    Cited by:

    1. Domenica Mirauda & Marco Ostoich, 2020. "MIMR Criterion Application: Entropy Approach to Select the Optimal Quality Parameter Set Responsible for River Pollution," Sustainability, MDPI, vol. 12(5), pages 1-22, March.
    2. Allison Lassiter & Nicole Leonard, 2022. "A systematic review of municipal smart water for climate adaptation and mitigation," Environment and Planning B, , vol. 49(5), pages 1406-1430, June.
    3. Martin Jason Luna Juncal & Timothy Skinner & Edoardo Bertone & Rodney A. Stewart, 2020. "Development of a Real-Time, Mobile Nitrate Monitoring Station for High-Frequency Data Collection," Sustainability, MDPI, vol. 12(14), pages 1-21, July.

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