Quality analysis of borewell water

Pure and clean potable water is a basic requirement, especially in regions where the groundwater is sourced from borewells as the primary source of water. The current study presents a detailed analysis of the quality of water in relation to dissolved oxygen, pH, turbidity, ammonia, sulfide, benzene, and electrical conductivity. Analysis of these crucial physicochemical parameters will be done with a calibrated set of sensors mounted for real-time precise monitoring of these key indicators. For the purpose of enhancing efficiency and accessibility of the operation, the initiative blends a hardware-centric sensing system with a trained machine learning model to interpret patterns in data and determine levels of water quality. The system is further enhanced by including a easy-to-use mobile application and web portal, where users can view real-time water quality parameters. The application will not only provide live sensor readings, but also will send notifications to the user when the values of the parameters cross their respective thresholds, thus enabling timely intervention. This approach which combines environmental surveillance, advanced data analysis, and human-centered design, is a cost-efficient and scalable solution to can be applied to both rural and urban populations. The framework described has tremendous potential in improving groundwater management practices and ensuring safe drinking water supply through automated, real-time monitoring.

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Publication Details

Journal
IET conference proceedings.
Published
2026-02-01
DOI
https://doi.org/10.1049/icp.2025.4698
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
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article

Quality analysis of borewell water

Kranti Ghag, Parth Mehta, Meera Narvekar, Jainam Gala et al.
IET conference proceedings.
Water Quality Monitoring Technologies
article

Quality analysis of borewell water

Kranti Ghag, Parth Mehta, Meera Narvekar, Jainam Gala, Ishaan Sheth, Kavya Shah
article en

Abstract

Pure and clean potable water is a basic requirement, especially in regions where the groundwater is sourced from borewells as the primary source of water. The current study presents a detailed analysis of the quality of water in relation to dissolved oxygen, pH, turbidity, ammonia, sulfide, benzene, and electrical conductivity. Analysis of these crucial physicochemical parameters will be done with a calibrated set of sensors mounted for real-time precise monitoring of these key indicators. For the purpose of enhancing efficiency and accessibility of the operation, the initiative blends a hardware-centric sensing system with a trained machine learning model to interpret patterns in data and determine levels of water quality. The system is further enhanced by including a easy-to-use mobile application and web portal, where users can view real-time water quality parameters. The application will not only provide live sensor readings, but also will send notifications to the user when the values of the parameters cross their respective thresholds, thus enabling timely intervention. This approach which combines environmental surveillance, advanced data analysis, and human-centered design, is a cost-efficient and scalable solution to can be applied to both rural and urban populations. The framework described has tremendous potential in improving groundwater management practices and ensuring safe drinking water supply through automated, real-time monitoring.

IET conference proceedings.Vol. 2025(43)
Dwarkadas J. Sanghvi College of Engineering (IN)
Openalex Percentile: Top 69%
Water Quality Monitoring Technologies
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