Artificial intelligence application to the water and wastewater treatment systems

The constantly growing urban scale and productivity have brought about greater demand for water resources, and human society is increasingly emphasizing automation and energy efficiency, which has led to enormous operational pressure and renovation needs for water and wastewater treatment systems. Existing water/wastewater treatment systems have been plagued by problems of inefficiency, high cost, and poor reliability due to lack of prompt and on-line water quality prediction technique, thus hindering the resources allocation and auto-feedback-regulation of the water and wastewater treatment processes. The emergence of artificial intelligence (AI) techniques offers novel and viable solutions to address these issues. Leveraging robust data analysis and processing capabilities, AI techniques such as machine learning and computer vision can extract valuable information from vast amounts of data, identify patterns and trends, enabling real-time monitoring and precise prediction for the state of water and wastewater, thereby enhancing the operational efficiency and reliability of such systems. Moreover, AI techniques can optimize resource allocation and achieve more intelligent automation control, thereby improving energy efficiency of such systems. Based on the differences in application objectives and scenarios, this chapter systematically summarizes the current applications of AI techniques to the water and wastewater treatment systems including water/wastewater treatment processes, urban drinking water systems (DWSs), and integrated urban drainage systems; analyzes the significance and challenges of AI techniques compared to traditional technologies; introduces potential improvement direction aimed at addressing these challenges; and finally gives the conclusions and the future perspective for AI development in such systems.