International Journal of Advances in Engineering & Scientific Research
Print ISSN : 2349 –4824
Online ISSN : 2349 –3607
Frequency : Continuous
Current Issue : Volume 12 , Issue 1
2025
Mr.C.Radhakrishnan, Adhithyan R, Dhanush Kumar M, Hitesh A.S
Mr.C.Radhakrishnan, Adhithyan R, Dhanush Kumar M, Hitesh A.S, Department of Computer Science and Engineering, Kongunadu College of Engineering and Technology, Tamilnadu, India
DOI : https://doi.org/10.5281/zenodo.14924994 Page No : 78-87
Published Online : 2025-02-25
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Traditional museum experiences often rely on static information displays or human guides, which can limit visitor engagement and accessibility. The challenge lies in providing a dynamic, personalized, and immersive storytelling experience that enhances learning while making museum visits more interactive. To address this, we propose an AR/VR-enabled Smart Museum Guide powered by Generative AI to revolutionize museum interactions through real-time, adaptive, and context-aware narratives. Our system leverages Augmented Reality (AR) and Virtual Reality (VR) technologies to provide an immersive and interactive museum experience. Visitors can use AR-enabled mobile applications or wear VR headsets to explore 3D models of artifacts, animations, and historical reconstructions, enhancing their understanding beyond static displays. A moveable AI-powered robotic guide will accompany visitors, using speech recognition and natural language processing (NLP) to engage in interactive conversations. The core of this system is Generative AI, which dynamically generates contextual narratives tailored to visitors’ interests, queries, and historical backgrounds. Transformer-based Models (GPT-4, LLaMA, or T5): Used for generating real-time, context-aware narratives based on visitor queries. BART (Bidirectional and Auto-Regressive Transformer): Helps in summarizing and rephrasing historical content dynamically. The AI model, trained on vast historical datasets, processes visitor inputs through deep learning algorithms, NLP models (such as GPT-based architectures), and knowledge graphs to provide accurate, coherent, and engaging storytelling. The system adapts its narration style based on visitor preferences, age groups, and even emotional responses detected through computer vision and sentiment analysis.
Keywords: Generative AI, AR, and VR, NLP, Computer Vision, Robotics and Path Planning and Interactive Museum Experience
