Introduction

Nowadays, Artificial intelligence (AI) is a developing technology. It is the process of mimicking human intellect for a range of uses. Artificial Intelligence is progressing quickly in comparison to conventional methods. AI has demonstrated its value in many industries, including banking and finance, space exploration, agriculture, and artificial creativity. AI is now making it’s place in the wastewater treatment sector because of its effectiveness, speed, and independence from human operations. The treatment of wastewater is a crucial step in lowering pollution and improving the quality of the water environment. The wastewater treatment system is unpredictable and variable because to the complexity of influent shock, natural circumstances, and wastewater treatment technology. This technology has been used to track the effectiveness of water treatment facilities in terms of efficiency metrics, as well as the calculation of chemical and biological oxygen demands (COD and BOD). Also, there have been two distinct phases to the development of machine learning (ML) in environmental science: a slow phase that lasted until the mid-2010s and a quick phase that followed. The swift change was prompted by the development of potent new machine learning techniques, which made it possible for ML to effectively address numerous issues where numerical and statistical models had proven inadequate. The application of ML on 2D or 3D data was significantly enhanced by deep convolutional neural network models. Since ML requires relatively short data sets in climate science, transfer learning has enabled ML to advance in this field. AI also has the potential to solve significant societal issues, such as sustainability, and will revolutionize business processes and entire industries. The climate problem and environmental degradation are incredibly complicated issues that need cutting-edge and creative solutions. We contend that AI may assist in the development of organizational procedures and individual habits that are culturally suitable in order to lower the energy and natural resource intensity of human activities. Our goal is to promote innovative research and useful applications of AI for environmental sustainability. In this chapter, we will discuss the development of AI in WWT, environmental science, and environmental sustainability.