Abstract: The current interior design of commercial buildings is facing innovative challenges, requiring a balance between aesthetics, functionality, and economic benefits. The design industry faces challenges in interdisciplinary integration, lack of standardized processes, and limitations of traditional design methods in complex situations. Although virtual reality technology provides new solutions, its integration difficulty, cost, and operational complexity constrain its widespread application. This study introduces a digitally twin-based augmented reality (AR) collaborative indoor design framework, addressing the decomposition of spatial planning for the complexity inherent in design processes. Subsequently, contextual data in the indoor design process is structured into an indoor design knowledge graph to elucidate information transmission and iterative mechanisms during collaborative design, thereby enhancing the situational adaptability of AR collaborative design. Utilizing a root anchor-based collaborative approach, multiple designers engage in spatial design collaboration within the AR environment. Real-time knowledge and data facilitated by the design knowledge graph contribute to collaborative decision-making, ensuring the quality and efficiency of collaborative design. Finally, exemplified by a complex interior design project for a commercial space, an AR-based collaborative digital twin (DT) interior design system is established, validating the effectiveness and feasibility of the proposed methodology. Through this approach, designers can preview and modify designs in a virtual environment, ultimately reducing errors, shortening design cycles, lowering costs, and enhancing user satisfaction.

Liqun Gao, “A Multi-Person Collaborative Design Method Driven by Augmented Reality” International Journal of Advanced Computer Science and Applications(IJACSA), 15(11), 2024. http://dx.doi.org/10.14569/IJACSA.2024.0151196

@article{Gao2024,
title = {A Multi-Person Collaborative Design Method Driven by Augmented Reality},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0151196},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0151196},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {11},
author = {Liqun Gao}
}