Artificial intelligence for wastewater treatment

Nguyen, XC; Nguyen, TTH; Tran, QB; Bui, XT; Ngo, HH; Nguyen, DD

Artificial intelligence for wastewater treatment

Nguyen, XC Nguyen, TTH Tran, QB Bui, XT Ngo, HH Nguyen, DD

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Publisher:: Elsevier
Publication Type:: Chapter
Citation:: Current Developments in Biotechnology and Bioengineering: Advances in Biological Wastewater Treatment Systems, 2022, pp. 587-608
Issue Date:: 2022-01-01

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Field	Value	Language
dc.contributor.author	Nguyen, XC
dc.contributor.author	Nguyen, TTH
dc.contributor.author	Tran, QB
dc.contributor.author	Bui, XT
dc.contributor.author	Ngo, HH
dc.contributor.author	Nguyen, DD
dc.date.accessioned	2023-04-12T06:28:26Z
dc.date.available	2023-04-12T06:28:26Z
dc.date.issued	2022-01-01
dc.identifier.citation	Current Developments in Biotechnology and Bioengineering: Advances in Biological Wastewater Treatment Systems, 2022, pp. 587-608
dc.identifier.isbn	9780323999434
dc.identifier.uri	http://hdl.handle.net/10453/169652
dc.description.abstract	Wastewater treatment is a complex system for which a vast amount of data has been generated through online sensors, providing the opportunity for applying artificial intelligence (AI) to improve the performance of the system. Applied AI was found to demonstrate a better potential for data analysis than conventional statistical assessment. This chapter outlines state-of-the-art development in the use of applied AI for wastewater treatment plants (WWTPs) with a focus on output, algorithms, data, and performance. Real applications of AI in WWTPs include prediction, soft sensors, intelligence control and optimization, and detection. This paper could therefore help environmental scientists, wastewater engineers, and practitioners in the better control and operation of WWTPs.
dc.language	en
dc.publisher	Elsevier
dc.relation.ispartof	Current Developments in Biotechnology and Bioengineering: Advances in Biological Wastewater Treatment Systems
dc.relation.isbasedon	10.1016/B978-0-323-99874-1.00008-7
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Artificial intelligence for wastewater treatment
dc.type	Chapter
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Civil and Environmental Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CTWW - Centre for Technology in Water and Wastewater Treatment
utslib.copyright.status	closed_access	*
dc.date.updated	2023-04-12T06:28:21Z
pubs.publication-status	Published

Abstract:

Wastewater treatment is a complex system for which a vast amount of data has been generated through online sensors, providing the opportunity for applying artificial intelligence (AI) to improve the performance of the system. Applied AI was found to demonstrate a better potential for data analysis than conventional statistical assessment. This chapter outlines state-of-the-art development in the use of applied AI for wastewater treatment plants (WWTPs) with a focus on output, algorithms, data, and performance. Real applications of AI in WWTPs include prediction, soft sensors, intelligence control and optimization, and detection. This paper could therefore help environmental scientists, wastewater engineers, and practitioners in the better control and operation of WWTPs.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/169652