Alexander Giovannelli

Elham Mohammadrezaei, Alexander Giovannelli, Logan Lane et al.

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.

Shakiba Davari, Daniel Stover, Alexander Giovannelli et al.

Recent advancements in Augmented Reality (AR) research have highlighted the critical role of context awareness in enhancing interface effectiveness and user experience. This underscores the need for intelligent AR (iAR) interfaces that dynamically adapt across various contexts to provide optimal experiences. In this paper, we (a) propose a comprehensive framework for context-aware inference and adaptation in iAR, (b) introduce a taxonomy that describes context through quantifiable input data, and (c) present an architecture that outlines the implementation of our proposed framework and taxonomy within iAR. Additionally, we present an empirical AR experiment to observe user behavior and record user performance, context, and user-specified adaptations to the AR interfaces within a context-switching scenario. We (d) explore the nuanced relationships between context and user adaptations in this scenario and discuss the significance of our framework in identifying these patterns. This experiment emphasizes the significance of context-awareness in iAR and provides a preliminary training dataset for this specific Scenario.