AI-Aided Integrated Terrestrial and Non-Terrestrial 6G Solutions for Sustainable Maritime Networking

被引:20
|
作者
Saafi, Salwa [1 ,3 ]
Vikhrova, Olga [4 ]
Fodor, Gabor [6 ,7 ]
Hosek, Jiri [2 ]
Andreev, Sergey [2 ,4 ,5 ]
机构
[1] Brno Univ Technol, Dept Telecommun, Brno, Czech Republic
[2] Brno Univ Technol, Brno, Czech Republic
[3] Tampere Univ, Unit Elect Engn, Tampere, Finland
[4] Tampere Univ, Tampere, Finland
[5] Tampere Univ, Commun Engn, Tampere, Finland
[6] Ericsson Res, Stockholm, Sweden
[7] KTH Royal Inst Technol, Stockholm, Sweden
来源
IEEE NETWORK | 2022年 / 36卷 / 03期
基金
芬兰科学院; 欧盟地平线“2020”;
关键词
Industries; 6G mobile communication; Automation; Ecosystems; Companies; Carbon dioxide; Energy efficiency;
D O I
10.1109/MNET.104.2100351
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The maritime industry is experiencing a technological revolution that affects shipbuilding, operation of both seagoing and inland vessels, cargo management, and working practices in harbors. This ongoing transformation is driven by the ambition to make the ecosystem more sustainable and cost-efficient. Digitalization and automation help achieve these goals by transforming shipping and cruising into a much more cost- and energy-efficient and decarbonized industry segment. The key enablers in these processes are always-available connectivity and content delivery services, which can not only aid shipping companies in improving their operational efficiency and reducing carbon emissions, but also contribute to enhanced crew welfare and passenger experience. Due to recent advancements in integrating high-capacity and ultra-reliable terrestrial and non-terrestrial networking technologies, ubiquitous maritime connectivity is becoming a reality. To cope with the increased complexity of managing these integrated systems, this article advocates the use of artificial intelligence and machine-learning-based approaches to meet the service requirements and energy efficiency targets in various maritime communications scenarios.
引用
收藏
页码:183 / 190
页数:8
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