Enhancing Museum Experiences with Augmented Reality and Machine Learning: A Case Study of Egyptian Cultural Heritage

Abstract

This study explores the application of augmented reality (AR) to enhance visitor engagement and accessibility in Egyptian museums, comparing two approaches: the Vuforia SDK and a deep learning model integrated with Unity. Addressing the need for innovative solutions to improve cultural heritage experiences, the research investigates how AR can deliver immersive and educational interactions with Egyptian artifacts. The Vuforia-based prototype offers structured content delivery using predefined image targets, while the deep learning model employs convolutional neural networks (CNNs) for real-time and adaptive object recognition across varied environments. User testing revealed that, although the Vuforia prototype is lightweight and user-friendly, the deep learning model outperformed it in accuracy and adaptability. However, its computational demands pose challenges for scalability. This paper highlights the transformative potential of deep learning-driven AR in cultural heritage and proposes strategies to optimize its adoption in the tourism sector.