A review of artificial intelligence in water purification and wastewater treatment: Recent advancements

Soma Safeer, Ravi P. Pandey, Bushra Rehman, Tuba Safdar, Iftikhar Ahmad, Shadi W. Hasan, Asmat Ullah

Research output: Contribution to journalReview articlepeer-review

102 Scopus citations

Abstract

Artificial intelligence (AI) is an emerging powerful novel technology that can model real-time problems involving numerous intricacies. The modeling capabilities of AI techniques are quite advantageous in water purification and wastewater treatment processes because the automation of such facilities resulted in easy and low cost operations; in addition to the significant reduction in the occurrence of human errors. AI technologies involve multi-linear or non-linear relationships and process dynamics that are usually impractical to model by conventional methodologies. This review presents a compendious synopsis of recent advancements and discoveries in various AI technologies applied to source water quality determination, coagulation/flocculation, disinfection, membrane filtration, desalination, modeling wastewater treatment plants, prediction of membrane fouling, removal of heavy metals, and monitoring of biological oxygen demand (BOD) and chemical oxygen demand (COD) levels. The analysis of the performance of various AI technologies in this review proves the successful implementation of these technologies in water treatment related applications. It also highlights the limitations that hinder their implementations in real-world water treatment systems.

Original languageBritish English
Article number102974
JournalJournal of Water Process Engineering
Volume49
DOIs
StatePublished - Oct 2022

Keywords

  • Artificial intelligence
  • Machine learning
  • Wastewater treatment
  • Water purification

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