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Artificial intelligence (AI) is nowadays an upcoming technology. It is a practice of simulating human intelligence for varied applications. When compared with the standard practices, AI is developing at a rapid rate. AI has proved its worth in several areas such as agriculture, automobile industry, banking and finance, space exploration, artificial creativity, etc. Owing to the efficiency, speed, and independence from human operations, AI is now entering the wastewater treatment sector. This technology has been used for monitoring the performance of the water treatment plants in terms of efficiency parameters, Biological Oxygen Demand (BOD) and Chemical Oxygen Demand (COD) determination, elimination of nitrogen and sulphur, prediction of turbidity and hardness, uptake of contaminants, etc., in the wastewater sector. Artificial Neural Networks (ANN), Fuzzy Logic Algorithms (FL), and Genetic Algorithms (GA) are the basic three models under AI predominantly used in the wastewater sector. Studies reveal that the determination coefficient values of 0.99 can be attained for COD, BOD, heavy metals and organics removal using ANN and hybrid intelligent systems. This review paper describes research with all the possible models of AI utilized in the water treatment which have enhanced the pollutant removal percentage accuracy of ranging from 84% to 90% and provided viewpoint on future directions of novel research, in the field with due focus on pollution remediation, cost effectiveness, energy economy, and water management.
Malviya et al. (Fri,) studied this question.
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