Automation and Optimization of Desalination Systems using Artificial Intelligence (AI) and Machine Learning (ML) Techniques

Freshwater is essential for humanity, but there isn't enough clean, drinkable water. Desalination is a big part of solving this problem because it turns seawater or brackish water into freshwater. But conventional desalination methods aren't always the best, and there is a lot of room for improvement. AI and machine learning (ML) can help these changes happen. Genetic Algorithms (GAs), Artificial Neural Networks (ANNs), and Fuzzy Logic Controllers (FLCs) are all examples of machine learning (ML) and artificial intelligence (AI) methods that can improve the desalination process and use less computing power. This paper talks about many ways that ML and AI can be used in desalination and provides a few examples of how these algorithms have worked well. The results are promising and show that things work much better in real life. AI and ML can help solve the problems that traditional desalination systems have and come up with new ways to make them work better. Artificial intelligence (AI) and machine learning (ML) could make desalination systems better and more automated in the future. The examined case studies demonstrate that AI and ML can significantly enhance plant performance. The evidence shows that using these technologies on a large scale is much better than current desalination methods.