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

  • Circular Economy for Global Water Security
  • Published:
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Abstract

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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Funding

The authors gratefully acknowledge financial support from the Universiti Sains Islam Malaysia and Universitas Airlangga.

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Authors and Affiliations

  1. Faculty of Science and Technology, Universiti Sains Islam Malaysia, Negeri Sembilan, Malaysia

    Waidah Ismail & Nurzi Juana Mohd Zaizi

  2. Faculty of Science and Technology, Universitas Airlangga, Indonesia Kampus C, Surabaya, Indonesia

    Waidah Ismail & Rimuljo Hendradi

  3. School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru, Malaysia

    Naghmeh Niknejad

  4. Azman Hashim International Business School, Universiti Teknologi Malaysia, Johor Bahru, Malaysia

    Mahadi Bahari

  5. Kulliyah of Science, International Islamic University Malaysia, Kuantan, Pahang, Malaysia

    Mohd Zamani Zulkifli

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  1. Waidah Ismail
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  2. Naghmeh Niknejad
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  3. Mahadi Bahari
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Contributions

Waidah Ismail: Writing - original draft, Naghmeh Niknejad: Methodology, data analysis, Mahadi Bahari: Conceptualization, Rimuljo Hendradi: Writing - reviewing and editing, Nurzi Juana Mohd Zaizi: Methodology, Mohd Zamani Zulkifli: Data analysis.

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Ismail, W., Niknejad, N., Bahari, M. et al. Water treatment and artificial intelligence techniques: a systematic literature review research. Environ Sci Pollut Res 30, 71794–71812 (2023). https://doi.org/10.1007/s11356-021-16471-0

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