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Water treatment and artificial intelligence techniques: a systematic literature review research

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dc.contributor.authorWaidah Ismailen_US
dc.contributor.authorNaghmeh Niknejaden_US
dc.contributor.authorMahadi Baharien_US
dc.contributor.authorRimuljo Hendradien_US
dc.contributor.authorNurzi Juana Mohd Zaizien_US
dc.contributor.authorMohd Zamani Zulkiflien_US
dc.date.accessioned2024-05-29T02:28:39Z
dc.date.available2024-05-29T02:28:39Z
dc.date.issued2023-06
dc.descriptionEnvironmental Science and Pollution Research Volume 30 Issue 28en_US
dc.description.abstractAs clean water can be considered among the essentials of human life, there is always a requirement to seek its foremost and high quality. Water primarily becomes polluted due to organic as well as inorganic pollutants, including nutrients, heavy metals, and constant contamination with organic materials. Predicting the quality of water accurately is essential for its better management along with controlling pollution. With stricter laws regarding water treatment to remove organic and biologic materials along with different pollutants, looking for novel technologic procedures will be necessary for improved control of the treatment processes by water utilities. Linear regression-based models with relative simplicity considering water prediction have been typically used as available statistical models. Nevertheless, in a majority of real problems, particularly those associated with modeling of water quality, non-linear patterns will be observed, requiring non-linear models to address them. Thus, artificial intelligence (AI) can be a good candidate in modeling and optimizing the elimination of pollutants from water in empirical settings with the ability to generate ideal operational variables, due to its recent considerable advancements. Management and operation of water treatment procedures are supported technically by these technologies, leading to higher efficiency compared to sole dependence on human operations. Thus, establishing predictive models for water quality and subsequently, more efficient management of water resources would be critically important, serving as a strong tool. A systematic review methodology has been employed in the present work to investigate the previous studies over the time interval of 2010–2020, while analyzing and synthesizing the literature, particularly regarding AI application in water treatment. A total number of 92 articles had addressed the topic under study using AI. Based on the conclusions, the application of AI can obviously facilitate operations, process automation, and management of water resources in significantly volatile contexts.en_US
dc.identifier.citationIsmail, W., Niknejad, N., Bahari, M., Hendradi, R., Zaizi, N. J. M., & Zulkifli, M. Z. (2023). Water treatment and artificial intelligence techniques: a systematic literature review research. Environmental Science and Pollution Research, 30(28), 71794–71812. https://doi.org/10.1007/s11356-021-16471-0en_US
dc.identifier.doi10.1007/s11356-021-16471-0
dc.identifier.issn1614-7499
dc.identifier.issue28
dc.identifier.urihttps://link.springer.com/article/10.1007/s11356-021-16471-0#citeas
dc.identifier.urihttps://www.scopus.com/record/display.uri?eid=2-s2.0-85116508123&origin=resultslist&sort=plf-f&src=s&sid=71f5605440be01176ae46999e0d32977&sot=b&sdt=b&s=TITLE-ABS-KEY%28Water+treatment+and+artificial+intelligence+techniques%3A+a+systematic+literature+review+research%29&sl=110&sessionSearchId=71f5605440be01176ae46999e0d32977
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/10773
dc.identifier.volume30
dc.language.isoen_USen_US
dc.publisherSpringeren_US
dc.relation.ispartofEnvironmental Science and Pollution Researchen_US
dc.subjectArtificial intelligence; Literature review; Water quality; Water treatmenten_US
dc.titleWater treatment and artificial intelligence techniques: a systematic literature review researchen_US
dc.typeArticleen_US
dspace.entity.typePublication

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