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    Water Quality Monitoring Using IoT & Machine Learning
    (IST-Africa 2022 Conference Proceedings, 2022) Omambia Andrew , Maake Benard & Wambua Anthony
    Safe water access is fundamental form of human survival and it is presented as a fundamental human right. As consumers use water, primarily sourced from pipes and springs located around towns, contamination, leakages, and pilferage happen. IoT and Machine Learning offer a promising solution to address these challenges. Premised on these technologies, the authors propose a system that monitors water quality and pilferage and wastage that uses machine learning algorithms for decision making.