The Role of Artificial Intelligence Driven 5G Networks in COVID-19 Outbreak: Opportunities, Challenges, and Future Outlook

被引:27
作者
Abubakar, Attai Ibrahim [1 ]
Omeke, Kenechi G. G. [1 ]
Ozturk, Metin [1 ]
Hussain, Sajjad [1 ]
Imran, Muhammad Ali [1 ]
机构
[1] Univ Glasgow, James Watt Sch Engn, Glasgow, Scotland
来源
FRONTIERS IN COMMUNICATIONS AND NETWORKS | 2020年 / 1卷
关键词
COVID-19; coronavirus; pandemic; 5G networks; self-organizing networks; artificial intelligence; machine learning; SOFTWARE-DEFINED NETWORKING; CELLULAR NETWORKS; MOBILITY PREDICTION; WIRELESS NETWORKS; BIG DATA; LEARNING DRIVEN; DENSE NETWORKS; FRAMEWORK; COMMUNICATION; AI;
D O I
10.3389/frcmn.2020.575065
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
There is no doubt that the world is currently experiencing a global pandemic that is reshaping our daily lives as well as the way business activities are being conducted. With the emphasis on social distancing as an effective means of curbing the rapid spread of the infection, many individuals, institutions, and industries have had to rely on telecommunications as a means of ensuring service continuity in order to prevent complete shutdown of their operations. This has put enormous pressure on both fixed and mobile networks. Though fifth generation mobile networks (5G) is at its infancy in terms of deployment, it possesses a broad category of services including enhanced mobile broadband (eMBB), ultra-reliable low-latency communications (URLLC), and massive machine-type communications (mMTC), that can help in tackling pandemic-related challenges. Therefore, in this paper, we identify the challenges facing existing networks due to the surge in traffic demand as a result of the COVID-19 pandemic and emphasize the role of 5G empowered by artificial intelligence in tackling these problems. In addition, we also provide a brief insight on the use of artificial intelligence driven 5G networks in predicting future pandemic outbreaks, and the development a pandemic-resilient society in case of future outbreaks.
引用
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页数:22
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