A survey of applications of artificial intelligence and machine learning in future mobile networks-enabled systems

Different fields have been thriving with the advents in mobile communication systems in recent years. These fields reap benefits of data collected by Internet of Things (IoT) in next generation (5G and 5BG) mobile networks. The IoT concept transforms different fields by providing large amount of dat...

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Main Authors: Yazici, İbrahim, Shayea, Ibraheem, Din, Jafri
Format: Article
Language:English
Published: Elsevier B.V. 2023
Subjects:
Online Access:http://eprints.utm.my/106806/1/JafriDin2023_ASurveyOfApplicationsOfArtificialIntelligence.pdf
http://eprints.utm.my/106806/
http://dx.doi.org/10.1016/j.jestch.2023.101455
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spelling my.utm.1068062024-07-30T08:27:06Z http://eprints.utm.my/106806/ A survey of applications of artificial intelligence and machine learning in future mobile networks-enabled systems Yazici, İbrahim Shayea, Ibraheem Din, Jafri TK Electrical engineering. Electronics Nuclear engineering Different fields have been thriving with the advents in mobile communication systems in recent years. These fields reap benefits of data collected by Internet of Things (IoT) in next generation (5G and 5BG) mobile networks. The IoT concept transforms different fields by providing large amount of data to be used in their operations. This is achieved by massively utilized sensors and mobile devices that acquire data from internet connected devices to keep track of physical systems. Hence, different use cases benefit from the data generated thanks to future mobile network systems. Intelligent Transportation Systems, Smart Energy, Digital Twins, Unmanned Aerial Vehicles (UAVs), Smart Health, Cyber Security are of significant use cases that big data plays an important role for them. Large amount of data entails more intelligent systems with respect to conventional methods, and it also entails highly reduced response time for use cases. Artificial intelligence and machine learning models are adept in satisfying the requirements of this big data situations for different use cases. In this sense, this paper provides a survey of machine learning and artificial intelligence applications for different use cases enabled by future mobile communication systems. An overview of machine learning types and artificial intelligence is presented to provide insights into the intelligent method concepts. Available studies are extensively summarized, and they are also grouped to provide a complete overview of the study. Discussions on the reviewed papers based on artificial intelligence and machine learning concepts are made, and some descriptive figures about the results of the discussions are also given in the paper. Finally, research challenges for artificial intelligence and machine learning applications in the use cases are introduced, future research directions and concluding remarks are presented accordingly. Elsevier B.V. 2023 Article PeerReviewed application/pdf en http://eprints.utm.my/106806/1/JafriDin2023_ASurveyOfApplicationsOfArtificialIntelligence.pdf Yazici, İbrahim and Shayea, Ibraheem and Din, Jafri (2023) A survey of applications of artificial intelligence and machine learning in future mobile networks-enabled systems. Engineering Science and Technology, an International Journal, 44 (NA). pp. 1-40. ISSN 2215-0986 http://dx.doi.org/10.1016/j.jestch.2023.101455 DOI : 10.1016/j.jestch.2023.101455
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Yazici, İbrahim
Shayea, Ibraheem
Din, Jafri
A survey of applications of artificial intelligence and machine learning in future mobile networks-enabled systems
description Different fields have been thriving with the advents in mobile communication systems in recent years. These fields reap benefits of data collected by Internet of Things (IoT) in next generation (5G and 5BG) mobile networks. The IoT concept transforms different fields by providing large amount of data to be used in their operations. This is achieved by massively utilized sensors and mobile devices that acquire data from internet connected devices to keep track of physical systems. Hence, different use cases benefit from the data generated thanks to future mobile network systems. Intelligent Transportation Systems, Smart Energy, Digital Twins, Unmanned Aerial Vehicles (UAVs), Smart Health, Cyber Security are of significant use cases that big data plays an important role for them. Large amount of data entails more intelligent systems with respect to conventional methods, and it also entails highly reduced response time for use cases. Artificial intelligence and machine learning models are adept in satisfying the requirements of this big data situations for different use cases. In this sense, this paper provides a survey of machine learning and artificial intelligence applications for different use cases enabled by future mobile communication systems. An overview of machine learning types and artificial intelligence is presented to provide insights into the intelligent method concepts. Available studies are extensively summarized, and they are also grouped to provide a complete overview of the study. Discussions on the reviewed papers based on artificial intelligence and machine learning concepts are made, and some descriptive figures about the results of the discussions are also given in the paper. Finally, research challenges for artificial intelligence and machine learning applications in the use cases are introduced, future research directions and concluding remarks are presented accordingly.
format Article
author Yazici, İbrahim
Shayea, Ibraheem
Din, Jafri
author_facet Yazici, İbrahim
Shayea, Ibraheem
Din, Jafri
author_sort Yazici, İbrahim
title A survey of applications of artificial intelligence and machine learning in future mobile networks-enabled systems
title_short A survey of applications of artificial intelligence and machine learning in future mobile networks-enabled systems
title_full A survey of applications of artificial intelligence and machine learning in future mobile networks-enabled systems
title_fullStr A survey of applications of artificial intelligence and machine learning in future mobile networks-enabled systems
title_full_unstemmed A survey of applications of artificial intelligence and machine learning in future mobile networks-enabled systems
title_sort survey of applications of artificial intelligence and machine learning in future mobile networks-enabled systems
publisher Elsevier B.V.
publishDate 2023
url http://eprints.utm.my/106806/1/JafriDin2023_ASurveyOfApplicationsOfArtificialIntelligence.pdf
http://eprints.utm.my/106806/
http://dx.doi.org/10.1016/j.jestch.2023.101455
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score 13.188404