Artificial intelligence in wastewater treatment plants: a review of current trends and adaptation strategies in the face of climate-driven rainfall fluctuations
Creators
- 1. TUBITAK Marmara Res Ctr, Climate Change & Life Sci, Kocaeli, Turkiye
- 2. Norwegian Univ Life Sci NMBU, Fac Sci & Technol, Dept Bldg & Environm Technol, Drobakveien 31, N-1433 As, Norway
- 3. Marche Polytech Univ, Dept Sci & Engn Mat Environm & Urban Planning SIMA, Ancona, Italy
Description
Wastewater treatment plants (WWTPs) are encountering challenges related to sustainability, efficiency, and economic viability due to stricter discharge standards and the impact of climate change, including heavy rainfall. Enhancing the resilience and performance of WWTPs is therefore crucial. This paper reviews the application of artificial intelligence (AI) models that can improve WWTP resilience in response to extreme rainfall events. It provides an overview of publications on digitalization of WWTPs over the past 33 years, proposes a new classification approach for AI models, and reviews existing AI applications aimed at improving the performance of WWTPs in response to extreme rainfall events. These applications highlight the importance of developing hybrid models that integrate AI with knowledge-driven models to improve accuracy. Furthermore, future AI research in WWTPs should incorporate hydrological forecasting to enable advance estimation of flow rates, and facilitate effective management.
Files
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Files
(364 Bytes)
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