¹Ù·Î°¡±â ¸Þ´º

¹Ù·Î°¡±â ¸Þ´º º»¹®³»¿ë ¹Ù·Î°¡±â ¸ÞÀθ޴º ¹Ù·Î°¡±â

ÁÖ¿ä¾È³»

HOME »çÀÌÆ®¸Ê ENGLISH

FONT SIZE

ÆùƮũ±â Å°¿ò 100% 110% 120% 130% 140% ÆùƮũ±â ÁÙÀÓ
¸Þ´ºº¸±â

±¹Á¦ÇмúÁö³í¹®

Á¦¸ñ
(2022) Digital Twin: Technology Evolution Stages and Implementation Layers with Technology Elements
ÀÛ¼ºÀÏ
2022-05-19
Á¶È¸¼ö
333


(2022) Digital Twin: Technology Evolution Stages and Implementation Layers with Technology Elements
 
Journal : IEEE Access, 10, 52609-52620
 
Author : Deuk-Young Jeong, Myung-Sun Baek (Member, IEEE), Tae-Beom Lim, Yong-Woon Kim
Se-Han Kim, Yong-Tae Lee(Member, IEEE), Woo-Sug Jung, In-Bok Lee*
 
 
 
Abstract

Digital twin has recently received considerable attention in various industry domains. The digital twin replicates physical objects (e.g., people, objects, spaces, systems, and processes) in the real world into digital objects in the digital world. It also provides various simulations to solve problems in the real world or to improve situational operations. Therefore, the digital twin is a convergence of various technologies, such as advanced machine-learning algorithms, data analytics, super-resolution visualization and modeling, and simulation. Because the digital twin is a complicated technology, a step-by-step implementation that includes many technology elements should be considered to create a digital twin model. In this study, implementation layers are introduced to guide practical implementations of the digital twin. In addition, technology elements were suggested for the presented implementation layers. Because the suggested technology elements include clear technology definitions, various application domains (e.g., energy, transportation, logistics, environment, manufacturing, and smart cities) can easily utilize the introduced implementation layers and technology elements according to the intended purpose. Furthermore, this paper describes the evolution of digital twins. Digital twin technology has evolved continuously since 2002, when the digital twin concept was first introduced. In the described evolution levels, we show the future aspects of digital twin technology, according to the technological evolution direction. Therefore, the digital twin model can be efficiently created by considering the evolution direction and future aspects by using the suggested digital twin evolution levels.

Keywords : Digital twin, digital twin technology evolution, implementation layer, technology elements
 
 
Download Link10.1109/ACCESS.2022.3174220
 
÷ºÎÆÄÀÏ:
÷ºÎÆÄÀÏÀÌ ¾ø½À´Ï´Ù.
´ÙÀ½±Û
(2022) Machine Learning Approach to Predict Air Temperature and Relative Humidity inside Mechanically and Naturally Ventilated Duck Houses: Application of Recurrent Neural Network
/ A3EL
(2022)Machine Learning Approach to Predict Air Temperature and Relative Humidity inside Mechanically and Naturally Ventilated Duck Houses: Application of Recurrent Neural Network Journal:Agriculture 12(3):318 Author:Sang-yeon Lee, In-bok Lee*, Uk-hyeon Yeo, Jun-gyu Kim, Rack-woo Kim ..
ÀÌÀü±Û
(2021) Development of three-dimensional visualisation technology of the aerodynamic environment in a greenhouse using CFD and VR technology, part 1:Development of VR a database using CFD
/ A3EL
(2021)Development of three-dimensional visualisation technology of the aerodynamic environment in a greenhouse using CFD and VR technology, part 1:Development of VR a database using CFD Journal:BIOSYSTEMS ENGINEERING, 207, 33~58 Author:Rack-Woo Kim,Jun-Gyu Kim,In-Bok Lee*,Uk-Hyeon Yeo,Sang-Yeo..