A-UDT: Augmented Urban Digital Twin for Visualization of Virtual and Real IoT Data

Seungyoub Ssin (), Hochul Cho () and Woontack Woo ()
Additional contact information
Seungyoub Ssin: KAIST KI-ITC ARRC
Hochul Cho: KAIST KI-ITC ARRC
Woontack Woo: KAIST KI-ITC ARRC

A chapter in Augmented Reality and Virtual Reality, 2021, pp 221-236 from Springer

Abstract: Abstract This paper introduces a method for developing Augmented Urban Digital Twin (A-UDT) for virtual and real Internet-of-Things (IoT) visualization and its benefits. It presents a method for generating virtual data using the Virtual IoT (VI) based on real IoT data, which can be used with cloud services. An urban digital twin is developed to find and simulate various problems arising in the city by extracting and visualizing data of the city. Designing urban digital twin has some challenging issues such as the difficulty of processing environmental information in real-time due to the absence of IoT support. This absence of IoT support can make problems like developing urban digital twin without knowing the types and scope of visualization. To overcome this limitation, we propose the augmented city miniature that uses generation system, process, storage, and network system of the component that generates VI with the same data structure as real IoT to generate and send data, and it simulates information on a 3D geographic map by sending the generated virtual data to the visualization part using Augmented Reality (AR). Urban digital twin based on the virtual data can make various simulations of city visualization that can be performed to discover required IoT and reduce development costs. A-UDT system can be applied to monitor and simulate diverse environmental information such as air quality, energy efficiency, object movements, and temperature distribution.

Keywords: Digital twin; Smart city; IoT; Augmented reality; Visualization; Simulation; 360 images (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:prochp:978-3-030-68086-2_17

Ordering information: This item can be ordered from
http://www.springer.com/9783030680862

DOI: 10.1007/978-3-030-68086-2_17

Access Statistics for this chapter

More chapters in Progress in IS from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().