id |
caadria2024_45 |
authors |
Hsieh, Tzu-Hsin and Jeng, Tay-Sheng |
year |
2024 |
title |
UrbanSight: Application of Digital Twin to Augmented Reality |
source |
Nicole Gardner, Christiane M. Herr, Likai Wang, Hirano Toshiki, Sumbul Ahmad Khan (eds.), ACCELERATED DESIGN - Proceedings of the 29th CAADRIA Conference, Singapore, 20-26 April 2024, Volume 1, pp. 271–280 |
doi |
https://doi.org/10.52842/conf.caadria.2024.1.271
|
summary |
BIM (Building Information Modelling) is currently used to construct building components, which does not provide good assistance for environmental sensing data and user feedback for management and maintenance. There are often problems with timely synchronization of building model information. In order to extend the BIM technology from the building design phase to the facility management phase, a 3D visualization platform is needed to optimize the efficiency of building management by introducing Digital Twin. This study therefore aims to combine Digital Twin developed through building information modelling with augmented reality (AR) headset to achieve automated control of building operation management for future urban governance. In this paper, we use Unity with Autodesk Forge API to build a BIM model with building information in the real site and display it in Microsoft HoloLens 2, which is a wearable device. First, Autodesk Forge API is used to build the monitoring platform of the field model. The data collected by the sensors are transferred to the IoT base station built by Raspberry pi to build the database. Then the digital twin dashboard interface on HoloLens 2 is displayed to control the sensors in the environment. This system breaks the 2D interface of the existing urban management interface and visualizes it in 3D in augmented reality (AR), creating a more intuitive and efficient way to manage smart cities. |
keywords |
Digital Twin, Augmented Reality (AR), Internet of Things (IoT), Smart City, Management Platform |
series |
CAADRIA |
email |
n76101012@gs.ncku.edu.tw |
full text |
file.pdf (2,145,998 bytes) |
references |
Content-type: text/plain
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last changed |
2024/11/17 22:05 |
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