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A new computer-based index for swimming pools’ environmental health assessment in big data environment by consensus-based fuzzy group decision-making models

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Abstract

Swimming pools are popularly used for sport and recreational purposes worldwide. These places influence swimmers’ health as they are considered public places. This study attempted to introduce a process mining framework which analyzes the environmental health status in swimming pools. In this context, a new numerical index namely Swimming Pool Environmental Health Index (SPEHI) was developed through which, big data extracted from checklists of environmental health inspection of swimming pools were analyzed in fuzzy environment. The methodology comprises MCDM (Multi- Criteria Decision-Making) approach including fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and fuzzy OWA (Ordered Weighting Average). The performance of this index was evaluated through an applied example on 12 swimming pools in Shiraz, Iran that was run for a three-year sequence from 2015 to 2017. Among 30 evaluation criteria used in this index, the greatest (0.61) and lowest (0.35) group weights were dedicated to “Residual chlorine biological water quality” and “existence of drinking water facilities”, respectively. For the study area, SPEHI showed a wide range of environmental health conditions between 37.8 (Relatively good) to 98.19 (Excellent). The extended index could shrink swimming pool’s big data to concise values which are interpretable for health experts and managers of sport sector. It helps figuring out the trends of hygiene conditions in a swimming pool over the time and easy access to compare a city’s swimming pools as well. The methodology is flexible in structure and thus, it could be applied for other sporting places.

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Notes

  1. Business Activity Monitoring

  2. Complex Event Processing

  3. Corporate Performance Management

  4. Continuous Process Improvement

  5. Business Process Improvement

  6. Total Quality Management

  7. Multi-Criteria Decision-Making

  8. Swimming Pools Environmental Health Index

  9. Multi-Criteria Group Decision-Making

  10. Fuzzy-Ordered Weighting Average

  11. Technique for Order of Preference by Similarity to Ideal Solution

  12. Decision Maker

  13. Standard Deviations

  14. Group Fuzzy Decision-Making

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Acknowledgements

This project was financially supported by Shiraz University of Medical Sciences with grant number 7261. Hereby, the authors would like to appreciate Dr. Mahdi Zarghami the faculty member of the University of Tabriz, Tabriz, Iran and Prof. Azizallah Memariani the faculty member of Kharazmi University, Tehran, Iran, for their guidance in the fuzzy MCDM modeling of this study and for sparing GFDM software.

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Authors and Affiliations

  1. Department of Environmental Health Engineering, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran

    Mohammad Ali Baghapour & Zohre Moeini

  2. Department of Environmental Health Engineering, School of Health, Larestan University of Medical Sciences, Larestan, Iran

    Mohammad Reza Shooshtarian

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  1. Mohammad Ali Baghapour
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  2. Zohre Moeini
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  3. Mohammad Reza Shooshtarian
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Correspondence to Mohammad Reza Shooshtarian.

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Baghapour, M.A., Moeini, Z. & Shooshtarian, M.R. A new computer-based index for swimming pools’ environmental health assessment in big data environment by consensus-based fuzzy group decision-making models. J Environ Health Sci Engineer 19, 1323–1332 (2021). https://doi.org/10.1007/s40201-021-00689-8

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  • DOI: https://doi.org/10.1007/s40201-021-00689-8

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