Internet of Digital Twin: Framework, Applications, and Enabling Technologies

Intelligent physical systems, such as smart vehicles and robotic arms, are increasingly integrated into both industrial and everyday applications. However, the systems typically face hardware limitations that constrain their computational capacities. Digital twin systems offer a solution by creating real-time digital replicas of physical systems that enhance computational efficiency, overcoming physical limitations. Moreover, multiple digital twins that hold complementary knowledge can conveniently collaborate to share information and computational resources, further improving the performance of physical systems by forming an Internet of Digital Twin (IoDT). This paper presents a comprehensive investigation of the digital twin network, tracing the evolution of digital twins and providing a classification of the key technologies, functional frameworks, and application domains of IoDT. This paper delves into the IoDT communication framework by studying the fundamental communication modes of IoDT, exploring its integration with advanced technologies such as edge computing, blockchain, 5G/6G networks, and machine learning to facilitate data transmission, interaction, and omni-directional sensing. By offering a broad perspective, the paper aims to deepen stakeholders’ understanding of current research and potential future developments, encouraging further exploration of IoDT technologies and their evolution.

Authors

Institutions

Publication Details

Journal
IEEE Communications Surveys & Tutorials
Published
2025-03-26
DOI
https://doi.org/10.1109/comst.2025.3554579
Citations
13
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
16.15

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Internet of Digital Twin: Framework, Applications, and Enabling Technologies

Longxiang Gao, Ruhan Liu, Youyang Qu, Tom H. Luan et al.
13 citations
IEEE Communications Surveys & Tutorials
Digital Transformation in Industry
16.15
article

Internet of Digital Twin: Framework, Applications, and Enabling Technologies

Longxiang Gao, Ruhan Liu, Youyang Qu, Tom H. Luan, Yong Xiang, Dongmei Zhao
article en
13 citations

Abstract

Intelligent physical systems, such as smart vehicles and robotic arms, are increasingly integrated into both industrial and everyday applications. However, the systems typically face hardware limitations that constrain their computational capacities. Digital twin systems offer a solution by creating real-time digital replicas of physical systems that enhance computational efficiency, overcoming physical limitations. Moreover, multiple digital twins that hold complementary knowledge can conveniently collaborate to share information and computational resources, further improving the performance of physical systems by forming an Internet of Digital Twin (IoDT). This paper presents a comprehensive investigation of the digital twin network, tracing the evolution of digital twins and providing a classification of the key technologies, functional frameworks, and application domains of IoDT. This paper delves into the IoDT communication framework by studying the fundamental communication modes of IoDT, exploring its integration with advanced technologies such as edge computing, blockchain, 5G/6G networks, and machine learning to facilitate data transmission, interaction, and omni-directional sensing. By offering a broad perspective, the paper aims to deepen stakeholders’ understanding of current research and potential future developments, encouraging further exploration of IoDT technologies and their evolution.

IEEE Communications Surveys & TutorialsVol. 28
Deakin University (AU), Qilu University of Technology (CN), Shandong Academy of Sciences (CN), Xi'an Jiaotong University (CN), McMaster University (CA)
National Natural Science Foundation of China, China Scholarship Council
Openalex Percentile: Top 1%
Digital Transformation in Industry
16.15
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.