The Application of Artificial Intelligence in the Effective Battery Life Cycle in the Closed Circular Economy Model—A Perspective
Global pollution of the environment is one of the most challenging environmental problems. Electronic-based population and anthropogenic activity are the main reasons for dramatically increasing the scale of waste generation, particularly battery waste. Improper battery waste disposal causes harmful...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Recycling |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2313-4321/7/6/81 |
| _version_ | 1797455555259793408 |
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| author | Agnieszka Pregowska Magdalena Osial Weronika Urbańska |
| author_facet | Agnieszka Pregowska Magdalena Osial Weronika Urbańska |
| author_sort | Agnieszka Pregowska |
| collection | DOAJ |
| description | Global pollution of the environment is one of the most challenging environmental problems. Electronic-based population and anthropogenic activity are the main reasons for dramatically increasing the scale of waste generation, particularly battery waste. Improper battery waste disposal causes harmful environmental effects. Due to the release of heavy metals, battery waste affects ecosystems and health. We are faced with the challenge of effective battery waste management, especially recycling, to prevent the depletion of natural resources and maintain ecological balance. Artificial Intelligence (AI) is practically present in all areas of our lives. It enables the reduction of the costs associated with various types of research, increases automation, and accelerates productivity. This paper reviews the representative research progress of effective Artificial Intelligence-based battery waste management in the context of sustainable development, in particular, the analysis of current trends, algorithm accuracy, and data availability. Finally, the future lines of research and development directions of human-oriented Artificial Intelligence applications both in the battery production process and in battery waste management are discussed. |
| first_indexed | 2024-03-09T15:55:00Z |
| format | Article |
| id | doaj.art-f1731814e6b94315908161413f805c1e |
| institution | Directory Open Access Journal |
| issn | 2313-4321 |
| language | English |
| last_indexed | 2024-03-09T15:55:00Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Recycling |
| spelling | doaj.art-f1731814e6b94315908161413f805c1e2023-11-24T17:43:39ZengMDPI AGRecycling2313-43212022-11-01768110.3390/recycling7060081The Application of Artificial Intelligence in the Effective Battery Life Cycle in the Closed Circular Economy Model—A PerspectiveAgnieszka Pregowska0Magdalena Osial1Weronika Urbańska2Institute of Fundamental Technological Research, Polish Academy of Sciences, Pawinskiego 5B Street, 02-106 Warsaw, PolandInstitute of Fundamental Technological Research, Polish Academy of Sciences, Pawinskiego 5B Street, 02-106 Warsaw, PolandFaculty of Environmental Engineering, Wrocław University of Science and Technology, Wybrzeże Wyspiańskiego 27, 50-370 Wroclaw, PolandGlobal pollution of the environment is one of the most challenging environmental problems. Electronic-based population and anthropogenic activity are the main reasons for dramatically increasing the scale of waste generation, particularly battery waste. Improper battery waste disposal causes harmful environmental effects. Due to the release of heavy metals, battery waste affects ecosystems and health. We are faced with the challenge of effective battery waste management, especially recycling, to prevent the depletion of natural resources and maintain ecological balance. Artificial Intelligence (AI) is practically present in all areas of our lives. It enables the reduction of the costs associated with various types of research, increases automation, and accelerates productivity. This paper reviews the representative research progress of effective Artificial Intelligence-based battery waste management in the context of sustainable development, in particular, the analysis of current trends, algorithm accuracy, and data availability. Finally, the future lines of research and development directions of human-oriented Artificial Intelligence applications both in the battery production process and in battery waste management are discussed.https://www.mdpi.com/2313-4321/7/6/81battery wastewaste managementartificial intelligencemachine learninggenetic programmingend-of-life |
| spellingShingle | Agnieszka Pregowska Magdalena Osial Weronika Urbańska The Application of Artificial Intelligence in the Effective Battery Life Cycle in the Closed Circular Economy Model—A Perspective Recycling battery waste waste management artificial intelligence machine learning genetic programming end-of-life |
| title | The Application of Artificial Intelligence in the Effective Battery Life Cycle in the Closed Circular Economy Model—A Perspective |
| title_full | The Application of Artificial Intelligence in the Effective Battery Life Cycle in the Closed Circular Economy Model—A Perspective |
| title_fullStr | The Application of Artificial Intelligence in the Effective Battery Life Cycle in the Closed Circular Economy Model—A Perspective |
| title_full_unstemmed | The Application of Artificial Intelligence in the Effective Battery Life Cycle in the Closed Circular Economy Model—A Perspective |
| title_short | The Application of Artificial Intelligence in the Effective Battery Life Cycle in the Closed Circular Economy Model—A Perspective |
| title_sort | application of artificial intelligence in the effective battery life cycle in the closed circular economy model a perspective |
| topic | battery waste waste management artificial intelligence machine learning genetic programming end-of-life |
| url | https://www.mdpi.com/2313-4321/7/6/81 |
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