Machine learning and artificial intelligence application in constructed wetlands for industrial effluent treatment: advances and challenges in assessment and bioremediation modeling

Abstract The combined knowledge of meteorological, water quality index, hydrodynamic, and biochemical processes in the constructed wetland (CW) can be utilized in mathematical models to evaluate the performance, design, processes, and functionality of wetlands to treat industrial effluents or polluted sites. The use of machine learning and artificial intelligence for the simulation of environmental and operational processes in wetlands has gained more attention for understanding the dynamics occurring in the water basins and to design possible interventions for successful management. In this chapter, a review has been performed to understand applicability, research advances, gaps, and major challenges of machine learning and artificial intelligence in CW studies for the treatment of industrial effluents. This chapter could be helpful for environmental scientists, biogeochemists, and industrial practitioners for the better management of polluted sites.