Water treatment and artificial intelligence techniques: a systematic literature review research
As 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 materi...
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my.utm.1072972024-09-01T06:56:14Z http://eprints.utm.my/107297/ Water treatment and artificial intelligence techniques: a systematic literature review research Ismail, Waidah Niknejad, Naghmeh Bahari, Mahadi Hendradi, Rimuljo Mohd. Zaizi, Nurzi Juana Zulkifli, Mohd. Zamani H Social Sciences (General) As 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. Springer Science and Business Media Deutschland GmbH 2023 Article PeerReviewed Ismail, Waidah and Niknejad, Naghmeh and Bahari, Mahadi and Hendradi, Rimuljo and Mohd. Zaizi, Nurzi Juana and Zulkifli, Mohd. Zamani (2023) Water treatment and artificial intelligence techniques: a systematic literature review research. Environmental Science and Pollution Research, 30 (28). pp. 71794-71812. ISSN 0944-1344 http://dx.doi.org/10.1007/s11356-021-16471-0 DOI : 10.1007/s11356-021-16471-0 |
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H Social Sciences (General) Ismail, Waidah Niknejad, Naghmeh Bahari, Mahadi Hendradi, Rimuljo Mohd. Zaizi, Nurzi Juana Zulkifli, Mohd. Zamani Water treatment and artificial intelligence techniques: a systematic literature review research |
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As 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. |
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Article |
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Ismail, Waidah Niknejad, Naghmeh Bahari, Mahadi Hendradi, Rimuljo Mohd. Zaizi, Nurzi Juana Zulkifli, Mohd. Zamani |
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Ismail, Waidah Niknejad, Naghmeh Bahari, Mahadi Hendradi, Rimuljo Mohd. Zaizi, Nurzi Juana Zulkifli, Mohd. Zamani |
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Ismail, Waidah |
title |
Water treatment and artificial intelligence techniques: a systematic literature review research |
title_short |
Water treatment and artificial intelligence techniques: a systematic literature review research |
title_full |
Water treatment and artificial intelligence techniques: a systematic literature review research |
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Water treatment and artificial intelligence techniques: a systematic literature review research |
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Water treatment and artificial intelligence techniques: a systematic literature review research |
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water treatment and artificial intelligence techniques: a systematic literature review research |
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Springer Science and Business Media Deutschland GmbH |
publishDate |
2023 |
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http://eprints.utm.my/107297/ http://dx.doi.org/10.1007/s11356-021-16471-0 |
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