The application of machine learning in nanoparticle treated water: A review
Pollution from industrial effluents and domestic waste are two of the most common sources of environmental pollutants. Due to the rising population and manufacturing industries, large amounts of pollutants were produced daily. Therefore, enhancements in wastewater treatment to render treated wastewa...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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EDP Sciences
2023-01-01
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| Series: | MATEC Web of Conferences |
| Online Access: | https://www.matec-conferences.org/articles/matecconf/pdf/2023/04/matecconf_cgchdrc2022_01009.pdf |
| _version_ | 1797843681799045120 |
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| author | Ngu Joyce Chen Yen Chan Mieow Kee Yeo Wan Sieng Nandong Jobrun |
| author_facet | Ngu Joyce Chen Yen Chan Mieow Kee Yeo Wan Sieng Nandong Jobrun |
| author_sort | Ngu Joyce Chen Yen |
| collection | DOAJ |
| description | Pollution from industrial effluents and domestic waste are two of the most common sources of environmental pollutants. Due to the rising population and manufacturing industries, large amounts of pollutants were produced daily. Therefore, enhancements in wastewater treatment to render treated wastewater and provide effective solutions are essential to return clean and safe water to be reused in the industrial, agricultural, and domestic sectors. Nanotechnology has been proven as an alternative approach to overcoming the existing water pollution issue. Nanoparticles exhibit high aspect ratios, large pore volumes, electrostatic properties, and high specific surfaces, which explains their efficiency in removing pollutants such as dyes, pesticides, heavy metals, oxygen-demanding wastes, and synthetic organic chemicals. Machine learning (ML) is a powerful tool to conduct the model and prediction of the adverse biological and environmental effects of nanoparticles in wastewater treatment. In this review, the application of ML in nanoparticle-treated water on different pollutants has been studied and it was discovered that the removal of the pollutants could be predicted through the mathematical approach which included ML. Further comparison of ML method can be carried out to assess the prediction performance of ML methods on pollutants removal. Moreover, future studies regarding the nanotoxicity, synthesis process, and reusability of nanoparticles are also necessary to take into consideration to safeguard the environment. |
| first_indexed | 2024-04-09T17:09:24Z |
| format | Article |
| id | doaj.art-fcf68b99b2fc458ebeb12748c1d4c3e2 |
| institution | Directory Open Access Journal |
| issn | 2261-236X |
| language | English |
| last_indexed | 2024-04-09T17:09:24Z |
| publishDate | 2023-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | MATEC Web of Conferences |
| spelling | doaj.art-fcf68b99b2fc458ebeb12748c1d4c3e22023-04-20T08:28:09ZengEDP SciencesMATEC Web of Conferences2261-236X2023-01-013770100910.1051/matecconf/202337701009matecconf_cgchdrc2022_01009The application of machine learning in nanoparticle treated water: A reviewNgu Joyce Chen Yen0Chan Mieow Kee1Yeo Wan Sieng2Nandong Jobrun3Department of Chemical and Energy Engineering, Faculty of Engineering and Sciences, Curtin UniversityCentre for Water Research, Faculty of Engineering, Built Environment and Information Technology, SEGi University. Jalan Teknologi, Kota DamansaraDepartment of Chemical and Energy Engineering, Faculty of Engineering and Sciences, Curtin UniversityDepartment of Chemical and Energy Engineering, Faculty of Engineering and Sciences, Curtin UniversityPollution from industrial effluents and domestic waste are two of the most common sources of environmental pollutants. Due to the rising population and manufacturing industries, large amounts of pollutants were produced daily. Therefore, enhancements in wastewater treatment to render treated wastewater and provide effective solutions are essential to return clean and safe water to be reused in the industrial, agricultural, and domestic sectors. Nanotechnology has been proven as an alternative approach to overcoming the existing water pollution issue. Nanoparticles exhibit high aspect ratios, large pore volumes, electrostatic properties, and high specific surfaces, which explains their efficiency in removing pollutants such as dyes, pesticides, heavy metals, oxygen-demanding wastes, and synthetic organic chemicals. Machine learning (ML) is a powerful tool to conduct the model and prediction of the adverse biological and environmental effects of nanoparticles in wastewater treatment. In this review, the application of ML in nanoparticle-treated water on different pollutants has been studied and it was discovered that the removal of the pollutants could be predicted through the mathematical approach which included ML. Further comparison of ML method can be carried out to assess the prediction performance of ML methods on pollutants removal. Moreover, future studies regarding the nanotoxicity, synthesis process, and reusability of nanoparticles are also necessary to take into consideration to safeguard the environment.https://www.matec-conferences.org/articles/matecconf/pdf/2023/04/matecconf_cgchdrc2022_01009.pdf |
| spellingShingle | Ngu Joyce Chen Yen Chan Mieow Kee Yeo Wan Sieng Nandong Jobrun The application of machine learning in nanoparticle treated water: A review MATEC Web of Conferences |
| title | The application of machine learning in nanoparticle treated water: A review |
| title_full | The application of machine learning in nanoparticle treated water: A review |
| title_fullStr | The application of machine learning in nanoparticle treated water: A review |
| title_full_unstemmed | The application of machine learning in nanoparticle treated water: A review |
| title_short | The application of machine learning in nanoparticle treated water: A review |
| title_sort | application of machine learning in nanoparticle treated water a review |
| url | https://www.matec-conferences.org/articles/matecconf/pdf/2023/04/matecconf_cgchdrc2022_01009.pdf |
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