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Artificial intelligence techniques applications in the wastewater: a comprehensive review

  • Yahya Zakur
  • , Fausto Márquez
  • , Ali Al-Taie
  • , Saif Alsaidi
  • , Abeer Alsadoon
  • , Seyed Bagher Mirashrafi
  • , Laith Flaih
  • , Yousif Zakoor
  • University of Mazandaran
  • University of Castilla-La Mancha
  • Wasit University
  • Asia Pacific International College
  • Cihan University-Erbil

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
12 Downloads (Pure)

Abstract

There are some challenges are firms the wastewater treatment, numerous hurdles concerning the enhancement of the energy efficiency, compliance with the increasingly stringent water quality regulations, and the maximizing resource recovery opportunities. In recent years, the computational models have garnered acknowledgment as potent instruments for tackling these various challenges, bolstering of the operational and economic effectiveness of the various wastewater treatment plants ("WWTPs"). Also, the review discusses the application of the various (AI) algorithms on the various wastewater treatment plants (WWTPs), predicting ("WWTP") effluent properties, the wastewater inflows, the anomaly detecting, and the energy optimization. The critical gaps and the future directions in the (AI) algorithms for the wastewater treatment, including the explain ability of the data-driven models or transfer Learning processes and reinforcement learning, are also addressed.
Original languageEnglish
Article number03006
Number of pages9
JournalE3S Web of Conferences
Volume605
DOIs
Publication statusPublished - 17 Jan 2025
Externally publishedYes
Event9th International Conference on Energy, Environment, Epidemiology and Information System, ICENIS 2024 - Hybrid, Semarang, Indonesia
Duration: 29 Oct 202430 Oct 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 6 - Clean Water and Sanitation
    SDG 6 Clean Water and Sanitation
  2. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

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