Optimizing wastewater treatment through artificial intelligence : recent advances and future prospects

© 2024 The Authors This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY-NC-ND 4.0), which permits copying and redistribution for non-commercial purposes with no derivatives, provided the original work is properly cited (http://creativecommons....

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Veröffentlicht in:Water science and technology : a journal of the International Association on Water Pollution Research. - 1986. - 90(2024), 3 vom: 14. Aug., Seite 731-757
1. Verfasser: Nagpal, Mudita (VerfasserIn)
Weitere Verfasser: Siddique, Miran Ahmad, Sharma, Khushi, Sharma, Nidhi, Mittal, Ankit
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2024
Zugriff auf das übergeordnete Werk:Water science and technology : a journal of the International Association on Water Pollution Research
Schlagworte:Journal Article Review artificial intelligence fault detection parameter monitoring pollutant removal wastewater treatment Wastewater
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520 |a © 2024 The Authors This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY-NC-ND 4.0), which permits copying and redistribution for non-commercial purposes with no derivatives, provided the original work is properly cited (http://creativecommons.org/licenses/by-nc-nd/4.0/). 
520 |a Artificial intelligence (AI) is increasingly being applied to wastewater treatment to enhance efficiency, improve processes, and optimize resource utilization. This review focuses on objectives, advantages, outputs, and major findings of various AI models in the three key aspects: the prediction of removal efficiency for both organic and inorganic pollutants, real-time monitoring of essential water quality parameters (such as pH, COD, BOD, turbidity, TDS, and conductivity), and fault detection in the processes and equipment integral to wastewater treatment. The prediction accuracy (R2 value) of AI technologies for pollutant removal has been reported to vary between 0.64 and 1.00. A critical aspect explored in this review is the cost-effectiveness of implementing AI systems in wastewater treatment. Numerous countries and municipalities are actively engaging in pilot projects and demonstrations to assess the feasibility and effectiveness of AI applications in wastewater treatment. Notably, the review highlights successful outcomes from these initiatives across diverse geographical contexts, showcasing the adaptability and positive impact of AI in revolutionizing wastewater treatment on a global scale. Further, insights on the ethical considerations and potential future directions for the use of AI in wastewater treatment plants have also been provided 
650 4 |a Journal Article 
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650 4 |a fault detection 
650 4 |a parameter monitoring 
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650 4 |a wastewater treatment 
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700 1 |a Siddique, Miran Ahmad  |e verfasserin  |4 aut 
700 1 |a Sharma, Khushi  |e verfasserin  |4 aut 
700 1 |a Sharma, Nidhi  |e verfasserin  |4 aut 
700 1 |a Mittal, Ankit  |e verfasserin  |4 aut 
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