Digital Twins: Modelling Languages Comparison

被引：0
|
作者：
Wahid, Abdul [1 ]
Zhu, Jiafeng [1 ]
Mauceri, Stefano [1 ]
Li, Lei [1 ]
Liu, Minghua [1 ]
机构：
[1] Natl Univ Ireland, Galway, Ireland
来源：
MACHINE LEARNING, OPTIMIZATION, AND DATA SCIENCE, LOD 2022, PT II | 2023年 / 13811卷
关键词：
Digital twin; Cyber-physical systems; System modelling; Decision support systems; Smart maintenance; NETWORKS; CHALLENGES; CAD;
D O I：
10.1007/978-3-031-25891-6_13
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A digital twin (DT) is a virtual representation of a physical entity that can be used to improve and automate decision-making. For instance, a DT can be used for real-time performance monitoring and optimisation. In this work, we investigate DTs from the point of view of the telecommunication industry (TI). First, we provide an introduction to the main concepts, tools, and applications related to DTs. Then, we clarify the benefits of DTs for the TI. Also, we identify the main challenges hindering widespread adoption of DTs within the TI. Finally, we argue that modelling languages are the key to overcome some of the main challenges. This provides a good starting point for discussion and further research.
引用
收藏
页码：169 / 178
页数：10
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