Applications of artificial intelligence in water treatment for optimization and automation of adsorption processes: Recent advances and prospects

Gulzar Alam, Ihsanullah Ihsanullah, Mu. Naushad, Mika Sillanpää

Research output: Contribution to journalReview articlepeer-review

219 Citations (Scopus)
1341 Downloads (Pure)

Abstract

Artificial intelligence (AI) has emerged as a powerful tool to resolve real-world problems and has gained tremendous attention due to its applications in various fields. In recent years, AI techniques have also been employed in water treatment and desalination to optimize the process and to offer practical solutions to water pollution and water scarcity. Applications of AI is also expected to reduce the operational expenditures of the water treatment process by decreasing the cost and optimizing chemicals usage. This review summarizes various AI techniques and their applications in water treatment with a focus on the adsorption of pollutants. Numerous AI models have successfully predicted the performance of different adsorbents for the removal of numerous pollutants from water. This review also highlighted some challenges and research gap concerning applications of AI in water treatment. Despite several advantages offered by AI, there some limitations that hindered the widespread applications of these techniques in real water treatment systems. The availability and selection of data, poor reproducibility, less evidence of applications in real water treatment are some of the key challenges that need to be addressed. Recommendations are made to ensure the successful applications of AI in future water-related technologies. This review is beneficial for environmental researchers, engineers, students, and all stakeholders in the water industry.

Original languageEnglish
Article number130011
Pages (from-to)1-19
Number of pages19
JournalChemical Engineering Journal
Volume427
Early online date24 Apr 2021
DOIs
Publication statusPublished (in print/issue) - 1 Jan 2022

Bibliographical note

Publisher Copyright:
© 2021 Elsevier B.V.

Keywords

  • Artifical intelligence
  • Optimization
  • Automation
  • Water treatment
  • Adsorption
  • Machine learning
  • Water pollution
  • Clean water
  • Artificial intelligence

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