Abstract
There are some challenges are firms the wastewater treatment, numerous hurdles concerning the enhancement of the energy efficiency, compliance with the increasingly stringent water quality regulations, and the maximizing resource recovery opportunities. In recent years, the computational models have garnered acknowledgment as potent instruments for tackling these various challenges, bolstering of the operational and economic effectiveness of the various wastewater treatment plants ("WWTPs"). Also, the review discusses the application of the various (AI) algorithms on the various wastewater treatment plants (WWTPs), predicting ("WWTP") effluent properties, the wastewater inflows, the anomaly detecting, and the energy optimization. The critical gaps and the future directions in the (AI) algorithms for the wastewater treatment, including the explain ability of the data-driven models or transfer Learning processes and reinforcement learning, are also addressed.
| Original language | English |
|---|---|
| Article number | 03006 |
| Number of pages | 9 |
| Journal | E3S Web of Conferences |
| Volume | 605 |
| DOIs | |
| Publication status | Published - 17 Jan 2025 |
| Externally published | Yes |
| Event | 9th International Conference on Energy, Environment, Epidemiology and Information System, ICENIS 2024 - Hybrid, Semarang, Indonesia Duration: 29 Oct 2024 → 30 Oct 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 6 Clean Water and Sanitation
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SDG 7 Affordable and Clean Energy
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