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DeepClassRooms: a deep learning based digital twin framework for on-campus class rooms
A lot of different methods are being opted for improving the educational standards through monitoring of the classrooms. The developed world uses Smart classrooms to enhance faculty efficiency based on accumulated learning outcomes and interests. Smart classroom boards, audio-visual aids, and multim...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer London
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8736310/ https://www.ncbi.nlm.nih.gov/pubmed/35017794 http://dx.doi.org/10.1007/s00521-021-06754-5 |
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author | Razzaq, Saad Shah, Babar Iqbal, Farkhund Ilyas, Muhammad Maqbool, Fahad Rocha, Alvaro |
author_facet | Razzaq, Saad Shah, Babar Iqbal, Farkhund Ilyas, Muhammad Maqbool, Fahad Rocha, Alvaro |
author_sort | Razzaq, Saad |
collection | PubMed |
description | A lot of different methods are being opted for improving the educational standards through monitoring of the classrooms. The developed world uses Smart classrooms to enhance faculty efficiency based on accumulated learning outcomes and interests. Smart classroom boards, audio-visual aids, and multimedia are directly related to the Smart classroom environment. Along with these facilities, more effort is required to monitor and analyze students’ outcomes, teachers’ performance, attendance records, and contents delivery in on-campus classrooms. One can achieve more improvement in quality teaching and learning outcomes by developing digital twins in on-campus classrooms. In this article, we have proposed DeepClass-Rooms, a digital twin framework for attendance and course contents monitoring for the public sector schools of Punjab, Pakistan. DeepClassRooms is cost-effective and requires RFID readers and high-edge computing devices at the Fog layer for attendance monitoring and content matching, using convolution neural network for on-campus and online classes. |
format | Online Article Text |
id | pubmed-8736310 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer London |
record_format | MEDLINE/PubMed |
spelling | pubmed-87363102022-01-07 DeepClassRooms: a deep learning based digital twin framework for on-campus class rooms Razzaq, Saad Shah, Babar Iqbal, Farkhund Ilyas, Muhammad Maqbool, Fahad Rocha, Alvaro Neural Comput Appl S.i. : Tam-Lhr A lot of different methods are being opted for improving the educational standards through monitoring of the classrooms. The developed world uses Smart classrooms to enhance faculty efficiency based on accumulated learning outcomes and interests. Smart classroom boards, audio-visual aids, and multimedia are directly related to the Smart classroom environment. Along with these facilities, more effort is required to monitor and analyze students’ outcomes, teachers’ performance, attendance records, and contents delivery in on-campus classrooms. One can achieve more improvement in quality teaching and learning outcomes by developing digital twins in on-campus classrooms. In this article, we have proposed DeepClass-Rooms, a digital twin framework for attendance and course contents monitoring for the public sector schools of Punjab, Pakistan. DeepClassRooms is cost-effective and requires RFID readers and high-edge computing devices at the Fog layer for attendance monitoring and content matching, using convolution neural network for on-campus and online classes. Springer London 2022-01-07 2023 /pmc/articles/PMC8736310/ /pubmed/35017794 http://dx.doi.org/10.1007/s00521-021-06754-5 Text en © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | S.i. : Tam-Lhr Razzaq, Saad Shah, Babar Iqbal, Farkhund Ilyas, Muhammad Maqbool, Fahad Rocha, Alvaro DeepClassRooms: a deep learning based digital twin framework for on-campus class rooms |
title | DeepClassRooms: a deep learning based digital twin framework for on-campus class rooms |
title_full | DeepClassRooms: a deep learning based digital twin framework for on-campus class rooms |
title_fullStr | DeepClassRooms: a deep learning based digital twin framework for on-campus class rooms |
title_full_unstemmed | DeepClassRooms: a deep learning based digital twin framework for on-campus class rooms |
title_short | DeepClassRooms: a deep learning based digital twin framework for on-campus class rooms |
title_sort | deepclassrooms: a deep learning based digital twin framework for on-campus class rooms |
topic | S.i. : Tam-Lhr |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8736310/ https://www.ncbi.nlm.nih.gov/pubmed/35017794 http://dx.doi.org/10.1007/s00521-021-06754-5 |
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