Leveraging Artificial Intelligence to Optimize Constructed Wetlands

Constructed wetlands, nature-based solutions for wastewater treatment, offer a sustainable and cost-effective approach to water pollution control. However, traditional constructed wetlands often suffer from limitations such as low treatment efficiency and long start-up times. Artificial intelligence (AI) has emerged as a promising tool to address these challenges and enhance the performance of constructed wetlands. This paper explores the state-of-the-art in AI applications for constructed wetlands. It delves into the potential of AI to optimize design, predict performance, and improve monitoring and control. Key findings include the successful application of AI in: design optimization, performance prediction, hydraulic performance simulation, specific pollutant removal, and integrated systems. While significant progress has been made, challenges such as data quality, model interpretability, and integration with existing infrastructure remain. Future research should focus on addressing these challenges and exploring new applications of AI to further enhance the performance and sustainability of constructed wetlands.

کلیدواژه ها:

Constructed Wetlands ، Artificial Intelligence ، Machine Learning ، Deep Learning ، Performance Prediction