Artificial intelligence applications in forward osmosis for water treatment: Recent developments and research directions
Saleh O. Alaswad, Eydhah Almatrafi
Abstract
Forward osmosis (FO) studies for water treatment until recently have been dominated by conventional empirical and mathematical modeling approaches. Artificial intelligence (AI) systems have the capacity to reduce complexity and improve accuracy of such models thereby making FO a viable commercial technology. In the past few years, there has been a surge of studies applying AI techniques to improve the FO process for water treatment. This paper offers a comprehensive review of these efforts and categorizes the existing research by type of AI technique, by application, by AI technique power, and by input and output parameters. For each classification, a thorough analysis is offered to indicate the main progress points as well as research gaps and inconsistencies. Overall, the study findings demonstrate that AI could be a breakthrough technology in commercializing FO with its strong predictive and analytical power. However, much more research is needed in terms of modeling approaches, methods, and parameters. Based on the findings, the study offers a roadmap to guide research of AI techniques for water treatment FO processes.