Artificial intelligence and edge computing for teaching quality evaluation based on 5G-enabled wireless communication technology
Abstract Cloud computing and artificial intelligence are now widely used for classroom teaching in higher learning institutes. The digital teaching supported to ICT technologies in colleges serves as a central point for the advancement of modern education; and has become as a mode of instruction and...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2023-03-01
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| Series: | Journal of Cloud Computing: Advances, Systems and Applications |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13677-023-00418-6 |
| _version_ | 1797859831344791552 |
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| author | Feng Li Caohui Wang |
| author_facet | Feng Li Caohui Wang |
| author_sort | Feng Li |
| collection | DOAJ |
| description | Abstract Cloud computing and artificial intelligence are now widely used for classroom teaching in higher learning institutes. The digital teaching supported to ICT technologies in colleges serves as a central point for the advancement of modern education; and has become as a mode of instruction and an approach to teaching. Digital teaching has emerged as a major driving force in the advancement of digital economy and digitization of education in colleges. In this paper, we investigate the movable information management system utilized in the digital teaching using edge computing and 5G wireless communication technology. Furthermore, we explain the idea of a mobile data scheme and presents a teaching platform based on the edge computing and 5G-enabled wireless communication technology. The main objective of this work is to develop a digital teaching framework for college students that, in fact, enables digital teaching, the collection, and incorporation of teaching information, the provision of modern education, and sharing of resources. Cutting-edge technology advancements in the educational platform have the potential to improve 5G communication. To implement the cutting-edge technology, all types of technological devices, smart devices, and gadgets from the Internet of Things (IoT) platform are used. We evaluated the proposed system through reasonable assumptions and numerical simulations. The experimental results reveal that the suggested system has significantly improved the teaching efficiency with which digital teaching management is managed in colleges. Moreover, the edge and 5G technology can significantly improve the system performance, in terms of response time, that can be as high as 11.45% when compared to non-cloud based approaches. |
| first_indexed | 2024-04-09T21:35:58Z |
| format | Article |
| id | doaj.art-8969664112f449319cf938582fb4a3c6 |
| institution | Directory Open Access Journal |
| issn | 2192-113X |
| language | English |
| last_indexed | 2024-04-09T21:35:58Z |
| publishDate | 2023-03-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Journal of Cloud Computing: Advances, Systems and Applications |
| spelling | doaj.art-8969664112f449319cf938582fb4a3c62023-03-26T11:17:54ZengSpringerOpenJournal of Cloud Computing: Advances, Systems and Applications2192-113X2023-03-0112111710.1186/s13677-023-00418-6Artificial intelligence and edge computing for teaching quality evaluation based on 5G-enabled wireless communication technologyFeng Li0Caohui Wang1The Graduate School of Wuhan Sports UniversityAcademy of Arts in Wuhan Sports UniversityAbstract Cloud computing and artificial intelligence are now widely used for classroom teaching in higher learning institutes. The digital teaching supported to ICT technologies in colleges serves as a central point for the advancement of modern education; and has become as a mode of instruction and an approach to teaching. Digital teaching has emerged as a major driving force in the advancement of digital economy and digitization of education in colleges. In this paper, we investigate the movable information management system utilized in the digital teaching using edge computing and 5G wireless communication technology. Furthermore, we explain the idea of a mobile data scheme and presents a teaching platform based on the edge computing and 5G-enabled wireless communication technology. The main objective of this work is to develop a digital teaching framework for college students that, in fact, enables digital teaching, the collection, and incorporation of teaching information, the provision of modern education, and sharing of resources. Cutting-edge technology advancements in the educational platform have the potential to improve 5G communication. To implement the cutting-edge technology, all types of technological devices, smart devices, and gadgets from the Internet of Things (IoT) platform are used. We evaluated the proposed system through reasonable assumptions and numerical simulations. The experimental results reveal that the suggested system has significantly improved the teaching efficiency with which digital teaching management is managed in colleges. Moreover, the edge and 5G technology can significantly improve the system performance, in terms of response time, that can be as high as 11.45% when compared to non-cloud based approaches.https://doi.org/10.1186/s13677-023-00418-6TeachingClassroom learningEdge computing5GWireless communication technologyEducation |
| spellingShingle | Feng Li Caohui Wang Artificial intelligence and edge computing for teaching quality evaluation based on 5G-enabled wireless communication technology Journal of Cloud Computing: Advances, Systems and Applications Teaching Classroom learning Edge computing 5G Wireless communication technology Education |
| title | Artificial intelligence and edge computing for teaching quality evaluation based on 5G-enabled wireless communication technology |
| title_full | Artificial intelligence and edge computing for teaching quality evaluation based on 5G-enabled wireless communication technology |
| title_fullStr | Artificial intelligence and edge computing for teaching quality evaluation based on 5G-enabled wireless communication technology |
| title_full_unstemmed | Artificial intelligence and edge computing for teaching quality evaluation based on 5G-enabled wireless communication technology |
| title_short | Artificial intelligence and edge computing for teaching quality evaluation based on 5G-enabled wireless communication technology |
| title_sort | artificial intelligence and edge computing for teaching quality evaluation based on 5g enabled wireless communication technology |
| topic | Teaching Classroom learning Edge computing 5G Wireless communication technology Education |
| url | https://doi.org/10.1186/s13677-023-00418-6 |
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