Title: Artificial Intelligence-based techniques to monitor and maintain the drinking water quality supplied to households

Authors: Yernagula Rajesh; Manasa Dwarampudi; Yernagula Pratap

Addresses: AU Trans-Disciplinary Research Hub, Andhra University, Visakhapatnam, Andhra Pradesh 530003, India ' Department of Civil Engineering, Gayatri Vidya Parishad College for Degree and PG Courses (A), Visakhapatnam, Andhra Pradesh 530045, India ' Department of Civil Engineering, Gayatri Vidya Parishad College for Degree and PG Courses (A), Visakhapatnam, Andhra Pradesh 530045, India

Abstract: The assessment of drinking water quality is a crucial issue due to the severe pollution of available water, which can cause diseases. Traditional methods of water quality measurement are labour-intensive and costly. This article proposes a real-time monitoring system using artificial intelligence (AI) approaches to address the issues related to drinking water quality. The system uses a multi-sensor array (MSA) and a raspberry Pi-based hardware platform to monitor water quality. The factors estimated are pH, total dissolved solids (TDS), and turbidity, which are the physical and chemical boundaries that most impact water quality. A fuzzy logic-based framework is developed to classify water quality into three classes: good, bad, and ordinary. The proposed method is compared to existing methods like MLP and SVM, and it produces better performance with accuracy, precision, recall, and F-score values of 98.724, 97.899, 95.154, and 98.875, respectively.

Keywords: drinking water; water quality; WQ; real-time monitoring; raspberry Pi-based platform; fuzzy interface system; python; multi-sensor array; MSA.

DOI: 10.1504/IJEWM.2025.149530

International Journal of Environment and Waste Management, 2025 Vol.38 No.3, pp.366 - 387

Received: 06 Dec 2023
Accepted: 26 Mar 2024
Published online: 05 Nov 2025 *

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