This review article focuses on the application of data-driven performance analyses in wastewater treatment plants (WWTPs). It synthesizes existing research on how data science techniques, such as machine learning and statistical modeling, are used to optimize the operational efficiency, reduce energy consumption, and improve the effluent quality of WWTPs. The paper discusses various data analysis methodologies and their effectiveness in identifying patterns, predicting failures, and enhancing overall plant performance, contributing to more sustainable water management practices.
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