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<p>This paper focuses on the functional characteristics of BIM technology, emphasizing the need to develop a combination of BIM technology tailored to the user’s interior design process. We utilize the hardware and software to establish the BIM technology environment, construct the interior design model using the Autodesk Revit software platform, import it into Lumion for color rendering, and utilize Navisworks Simulate software to gather project data and monitor the interior design project’s progress. Autodesk Ecotect software was used to find out how lighting affected the interior design using BIM technology. Next, an interior layout optimization model based on the improved whale algorithm was made to solve the interior layout problem, and the impact of using AI was confirmed. The data show that the error range for the daylighting coefficient using BIM technology and the old method is between 0.04 and 0.91. The old method takes 131 minutes longer than BIM technology. This means that the BIM-based lighting simulation model pre-processing process is still much more efficient than the old method. Furthermore, this paper maintains all the model’s index values above 0.68, demonstrating the model’s ability to achieve a reasonable interior space layout while simultaneously enhancing both the layout speed and the layout effect.</p>
</abstract>

This paper focuses on the functional characteristics of BIM technology, emphasizing the need to develop a combination of BIM technology tailored to the user’s interior design process. We utilize the hardware and software to establish the BIM technology environment, construct the interior design model using the Autodesk Revit software platform, import it into Lumion for color rendering, and utilize Navisworks Simulate software to gather project data and monitor the interior design project’s progress. Autodesk Ecotect software was used to find out how lighting affected the interior design using BIM technology. Next, an interior layout optimization model based on the improved whale algorithm was made to solve the interior layout problem, and the impact of using AI was confirmed. The data show that the error range for the daylighting coefficient using BIM technology and the old method is between 0.04 and 0.91. The old method takes 131 minutes longer than BIM technology. This means that the BIM-based lighting simulation model pre-processing process is still much more efficient than the old method. Furthermore, this paper maintains all the model’s index values above 0.68, demonstrating the model’s ability to achieve a reasonable interior space layout while simultaneously enhancing both the layout speed and the layout effect.

A study on the application of AI in modern interior design and its impact on design efficiency

Applied Mathematics and Nonlinear Sciences

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

This paper focuses on the functional characteristics of BIM technology, emphasizing the need to develop a combination of BIM technology tailored to the user’s...

A study on the application of AI in modern interior design and its impact on design efficiency

Publicado en línea: 05 ago 2024

Páginas: -

Recibido: 12 abr 2024

Aceptado: 10 jul 2024

DOI: https://doi.org/10.2478/amns-2024-2242

Palabras clave
BIM technology, Whale algorithm, Layout optimization model, Interior design, Design efficiency

© 2024 Zijun Zhao, published by Sciendo

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

A study on the application of AI in modern interior design and its impact on design efficiency

Publicado en línea: 05 ago 2024

Páginas: -

Recibido: 12 abr 2024

Aceptado: 10 jul 2024

DOI: https://doi.org/10.2478/amns-2024-2242

Palabras claveBIM technology, Whale algorithm, Layout optimization model, Interior design, Design efficiency

© 2024 Zijun Zhao, published by Sciendo

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

Palabras clave
BIM technology, Whale algorithm, Layout optimization model, Interior design, Design efficiency