Can machine language and artificial intelligence revolutionize process automation for water treatment and desalination?

Abstract Artificial intelligence (AI) is a powerful tool that is commonly applied in engineering multi-disciplines owing to its functionality to resolve real-world problems where deterministic solutions are arduous to achieve. Revolution in water treatment and desalination process automation has been emerging recently. Several challenges are present in the water sector related to data structuring and smart water services through which AI would have great potential once those issues are addressed. The distinctive tools of AI, mainly; artificial neural networks (ANNs), as a regression model, and genetic algorithm (GA), as one of the global optimization techniques, have been immensely applied in desalination and water treatment for multi-purpose applications. Modelling desalination and water treatment processes and optimizing the operating condition are few among the many applications. In the current review, paramount applications of AI tools in desalination and water treatment have been thoroughly reviewed. In addition, benchmarking ANNs with the conventional modelling approaches were highlighted, along with the shortcomings and challenges expected to associate with these common tools in some complex nature practical application. It was concluded that the use of AI tools will undoubtedly pave the way in the water sector towards better operation, process automation, and water resources management in an increasingly volatile environment. Highlights • Machine learning and process automation prospects in desalination. • Limitations of classical approaches in predicting membrane characteristics and performance. • Modelling of ions and pollutant removal by Artificial neural network and genetic algorithms. • Statistical algorithms for optimizing desalination plants. • Cost and efficiency prediction by artificial intelligence for desalination application. [ABSTRACT FROM AUTHOR]