Artificial intelligence in wastewater treatment: Research trends and future perspectives through bibliometric analysis - Abdullah O. Baarimah; Mahmood A. Bazel; Wesam Salah Alaloul; Motasem Y.D. Alazaiza; Tharaa M. Al-Zghoul; Basheer Almuhaya; Arsalaan Khan; Ahmed W. Mushtaha (Case Studies in Chemical and Environmental Engineering)
The world faces growing water scarcity and the need for efficient wastewater treatment. The application of advanced artificial intelligence (AI) techniques holds great promise in optimizing processes, enhancing predictive capabilities, and supporting informed decision-making in this critical domain. This study, which focuses on research trends and developments in the use of AI for wastewater treatment, provides a thorough bibliometric analysis of 368 documents from the Scopus database between 2015 and 2024. The analysis reveals a significant increase in research output, peaking at 93 publications in 2023. This suggests growing interest and focus in leveraging AI techniques to address wastewater management challenges. According to the data, the most important journals in this field are Chemosphere, Water Science and Technology, and the Journal of Environmental Management. Significant contributors to the study were China, India, and the US, with the University of Johannesburg emerging as the most influential institution. The main research direction in this field is properly indicated by the frequently used keywords ''artificial intelligence,'' ''wastewater treatment,'' and ''machine learning,'' according to the analysis of keywords indicating the technological approaches being explored. Adsorption, microalgae, and anaerobic digestion are common methods that are gaining popularity. The most frequently studied wastewater contaminants in recent years have included heavy metals and nutrients. The findings of this analysis provide valuable insights that can guide future research priorities, inform the development of effective AI-driven solutions, and contribute to more sustainable water management practices.