Artificial intelligence integration in conventional wastewater treatment techniques: techno-economic evaluation, recent progress and its future direction

Artificial intelligence (AI) is currently making an appearance in the wastewater treatment industry because of its effectiveness, speed, and independence from human intervention. This in-depth analysis examines the underlying ideas of AI and how they apply to the field of wastewater treatment. This review explores cutting-edge AI technology, focusing on water quality monitoring, where AI-driven innovations have completely changed how water quality data is gathered and analysed. Also, it reviewed AI applications in adsorption, coagulation for removal of microorganism, heavy metals, organic and inorganic chemicals, dyes, and other emerging pollutants present in water and its process optimisation, prediction of capacity and efficiency, real-time monitoring, and better material selection in all conventional techniques. With a focus on intelligent electrode material selection, electrochemical process optimisation, and electrochemical system predictive maintenance, we examine the synergy of AI in electrochemical wastewater treatment. The paper also looks at AI applications in various areas of wastewater treatment, including advanced oxidation processes (AOPs), AI-based membrane material selection, and biological wastewater treatment. This includes cost–benefit analysis of AI deployment in wastewater treatment facilities, together with AI-driven financial optimisation and return on investment analysis, because economic factors are vital for technological acceptance. At the end of the article potential future possibilities for AI applications in this industry and analysing the difficulties encountered while integrating AI in wastewater treatment has been highlighted. Overall, incorporating AI into wastewater treatment procedures has a lot of potential to improve global sustainability, efficiency, and environmental protection.