<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In this paper, the digital twin platform for the indoor environment is constructed by combining digital twin technology and modern indoor environment elements to innovate the modern indoor environment design method. The digital twin platform is designed for modern indoor environments in two aspects: data acquisition and 3D model visualization for indoor environments. The indoor environment data are collected, cleaned and quasi-exchanged using sensors, the collected multi-source heterogeneous data of the indoor environment are fused by the time alignment method, and the 3D model of the indoor environment is driven by the design of the 3D model’s operations of translation, rotation and scaling. On this basis, the performance of the indoor environment digital twin platform is analyzed, and the data acquisition method and driving effects of the 3D model are explored. The results show that the data transmission measurement delay is within 20ms, the display delay is within 70ms, the transmission frames per second are basically stabilized at about 200FPS, 100FPS, 60FPS, the accuracy reaches 0.9 in the case of multiple data acquisition, and the fusion speed is about 3.4m/s, and the success rate of the driving operation of the overall three-dimensional model of the indoor environment is all greater than 0.96.</p>
</abstract>

In this paper, the digital twin platform for the indoor environment is constructed by combining digital twin technology and modern indoor environment elements to innovate the modern indoor environment design method. The digital twin platform is designed for modern indoor environments in two aspects: data acquisition and 3D model visualization for indoor environments. The indoor environment data are collected, cleaned and quasi-exchanged using sensors, the collected multi-source heterogeneous data of the indoor environment are fused by the time alignment method, and the 3D model of the indoor environment is driven by the design of the 3D model’s operations of translation, rotation and scaling. On this basis, the performance of the indoor environment digital twin platform is analyzed, and the data acquisition method and driving effects of the 3D model are explored. The results show that the data transmission measurement delay is within 20ms, the display delay is within 70ms, the transmission frames per second are basically stabilized at about 200FPS, 100FPS, 60FPS, the accuracy reaches 0.9 in the case of multiple data acquisition, and the fusion speed is about 3.4m/s, and the success rate of the driving operation of the overall three-dimensional model of the indoor environment is all greater than 0.96.

The Embodiment and Innovation of Digital Twin Platform in Modern Interior Environment Design

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

In this paper, the digital twin platform for the indoor environment is constructed by combining digital twin technology and modern indoor environment elements...

The Embodiment and Innovation of Digital Twin Platform in Modern Interior Environment Design

Publié en ligne: 09 déc. 2023

Pages: -

Reçu: 26 févr. 2023

Accepté: 19 juin 2023

DOI: https://doi.org/10.2478/amns.2023.2.01420

Mots clés
Digital twin technology, Multi-source heterogeneous data, Temporal alignment, 3D model-driven, Interior environment design

© 2023 Xiaoyao Chen et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

The Embodiment and Innovation of Digital Twin Platform in Modern Interior Environment Design

Publié en ligne: 09 déc. 2023

Pages: -

Reçu: 26 févr. 2023

Accepté: 19 juin 2023

DOI: https://doi.org/10.2478/amns.2023.2.01420

Mots clésDigital twin technology, Multi-source heterogeneous data, Temporal alignment, 3D model-driven, Interior environment design

© 2023 Xiaoyao Chen et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
Digital twin technology, Multi-source heterogeneous data, Temporal alignment, 3D model-driven, Interior environment design