A Review of Artificial Intelligence Applications in Modeling and Removal Processes of Pollutants Soluble in Water and Wastewater

Artificial intelligence can learn, infer, and make intelligent decisions. One of the main advantages of artificial intelligence is that by extracting patterns and learning from data, it can correctly diagnose and predict problems. Artificial intelligence has been noticed as a tool to better solve problems due to its many applications in various fields. In recent years, this algorithm has been used in the area of water and wastewater treatment processes to model, optimize, and provide solutions for strategic management to prevent and reduce water pollution, reduce operating costs, and optimize the use of chemical substances. Various artificial intelligence algorithms in water and wastewater treatment processes focus on pollutant absorption and, in most cases, on the performance of adsorbents to remove organic and metal pollutants. This study presents various artificial intelligence models, their advantages, limitations, challenges, and research problems of models in water purification processes. Considering the many advantages of artificial intelligence, this algorithm with limitations can prevent its expansion in water purification processes. Regardless of these limitations, current research progress shows that artificial intelligence tools have great potential to revolutionize wastewater treatment processes and programs. According to the models reviewed in this research, the use of DNN, ANN models, and combined artificial intelligence techniques are good options to achieve more accurate predictions.