AR-Enhanced Digital Menu System: Integrating 3D Visualization with AI-Driven Ingredient Detection
Year: 2025
Type: conference-paper
Abstract: : The aim of our study is to present an AR menu system for web based sophisticated implementation and implement AI-supported ingredient detection as world changer in dining using on Android system [21]. In order to get around traditional menu limitations the system translates 3D views and offers nutritional context live, helping customers make informed decisions. Our implementation uses Three.js for rendering and support to serve realistic looking food models along with interactive interfaces providing a unified experience for the full range of ingredients and nutrition Meta masks. Rendering performance, AI detection accuracy and user interactions on different devices/screens was measured as part of the assessment. The results showed a remarkable usability (97.2 % of QR code scanning, 94.3% ingredient detection accuracy and stable 55+ FPS performance on different devices). This implementation highlights a use case for everyday web tech to create an inclusive experience at a dine in, combative of todays state of digital menu systems hospitality.
Authors: S, Adiithyan, Philip, Ankitha
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6893295016
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