Abstract
The use of a water storage system to store and distribute water is a widely adopted approach in numerous households.The issue of assessing the water quality in the tank prior to its distribution to households remains unresolved.The advanced method of monitoring and managing water resources is through the implementation of the intelligent system for detecting water quality and level is proposed in this paper. The proposed approach employs hybrid classifiers which integrate three machine learning algorithms to determine the quality of the water according to the sensed metrics such as turbidity, pH level, and total dissolved solids. The deployment of machine learning algorithms aids in the decision-making process about water quality and gives water treatment facilities precise and trustworthy information. The novelty of the proposed system includes machine learning based continuous monitoring and depends on the water quality identified water can be directed for drinking or household purposes. The benefits of this novel water quality monitoring system include low power usage, zero carbon emissions, and great adaptability.
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The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
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The Code created and compiled during the current study are available from the corresponding author on reasonable request.
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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Siva and Sivasubash. The first draft of the manuscript was written by Sathananthavathi and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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Sathananthavathi, V., Shiva, A. & Sivasubash, S.S. Intelligent Water Quality and Level Detection System Using Hybrid Classifier. Wireless Pers Commun 135, 1909–1924 (2024). https://doi.org/10.1007/s11277-024-11099-y
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DOI: https://doi.org/10.1007/s11277-024-11099-y