A digital twin based approach to smart lighting design
This work addresses lighting design for architectural settings, but it is incremental as it applies existing methods like CLIP to a new domain.
The paper tackled the problem of smart lighting design by using a digital twin and CLIP neural network to measure similarity between real and virtual lighting configurations, achieving a similarity value of over 87% in a case study.
Lighting has a critical impact on user mood and behavior, especially in architectural settings. Consequently, smart lighting design is a rapidly growing research area. We describe a digital twin-based approach to smart lighting design that uses an immersive virtual reality digital twin equivalent (virtual environment) of the real world, physical architectural space to explore the visual impact of light configurations. The CLIP neural network is used to obtain a similarity measure between a photo of the physical space with the corresponding rendering in the virtual environment. A case study was used to evaluate the proposed design process. The obtained similarity value of over 87% demonstrates the utility of the proposed approach.