The use of artificial intelligence in water treatment: a systematic review
DOI:
https://doi.org/10.59464/2359-4632.2025.3249Keywords:
Water management, Process optimization, Control and monitoring, Neural networks, ArtificialAbstract
The use of Artificial Intelligence (AI) in water treatment has shown promise for optimizing, monitoring, and controlling water purification processes. Objective: This study aimed to review the current scenario of AI application in water treatment, identifying challenges and future prospects. Method: An integrative review was conducted between July and December 2023 in the Science Direct and CAPES databases, using the descriptors “Artificial Intelligence” and “Water Treatment.” Results: Of the 390 articles initially selected, 12 met the inclusion criteria, addressing the relationship between AI and water treatment processes. The studies indicate that techniques such as artificial neural networks, fuzzy logic, and machine learning algorithms are the most widely applied, contributing to greater operational efficiency, failure prediction, input dosage control, and real-time monitoring. The main challenges identified include the availability of reliable data, methodological standardization, and full-scale validation. Among the results observed, the ability of AI to reduce costs, increase system reliability, and support strategic decisions in water management stands out. The analysis shows that the application of AI can optimize processes, improve water quality control, and promote water sustainability, provided that robust and adaptable models are employed. Conclusion: The review highlights the importance of advancing applied research, validating technologies in real contexts, and points to AI as a relevant strategy for water security and operational efficiency in water treatment systems.
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