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Water Supply Chain Resource Management in Cities Using Data Mining Techniques

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  • Reshu Agarwal

    (Amity Institute of Information Technology, Amity University, Noida, India)

  • Adarsh Dixit

    (Amity Institute of Information Technology, Amity University, Noida, India)

Abstract

This paper presents a comparative research study between a number of data mining techniques, knowledge discovery tools, data analysis and software packages to be used in a Decision Support System (DSS) for Smart water supply chain resources management. The case study deals with the evaluation and comparative research of water quality of city water supply within New Delhi city area. In the case of New-Delhi water supply alternative actions for improving of water supply and quality are defined for efficient supply in distributed area. The real time water quality monitor uses given standards by Water Quality Index (WQI) and Statistical analysis done on it suggests the shortest path between supply station and local area distribution Centre by used WEKA mining tool (decision tree) and OLAP. The results show that the city water isn't supplied efficiently in the city and not within the standard quality criteria of (WHO) standards and Indian standards. Leanings and research challenges observed during this comparative study have also been enumerated.

Suggested Citation

  • Reshu Agarwal & Adarsh Dixit, 2023. "Water Supply Chain Resource Management in Cities Using Data Mining Techniques," International Journal of Information Retrieval Research (IJIRR), IGI Global, vol. 13(1), pages 1-14, January.
    • Handle: RePEc:igg:jirr00:v:13:y:2023:i:1:p:1-14
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