Zakur, Yahya and Márquez, Fausto and Al-taie, Ali and Alsaidi, Saif and Alsadoon, Abeer and Bagher Mirashrafi, Seyed and R.Flaih, Laith and Zakoor, Yousif (2025) Artificial Intelligence Techniques Applications in the Wastewater: A Comprehensive Review. In: The 9th International Conference on Energy, Environment, Epidemiology, and Information System, 29–30_10-2024, Diponegoro University, Semarang, Indonesia.
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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.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | Artificial Intelligence, Wastewater Treatment, Machine Learning, Neural Networks, Data Analysis, Environmental Engineering, Process Optimization, Water Quality, Automation, Predictive Modeling |
| Subjects: | Q Science > Q Science (General) Q Science > QE Geology T Technology > TD Environmental technology. Sanitary engineering |
| Divisions: | Department of Computer Science > Research papers |
| Depositing User: | ePrints Depositor |
| Date Deposited: | 06 Aug 2025 11:51 |
| Last Modified: | 06 Aug 2025 11:51 |
| URI: | https://eprints.cihanuniversity.edu.iq/id/eprint/3921 |
