Sadia Nur Amin
An Augmented Reality-Based Approach for Designing Interactive Food Menu of Restaurant Using Android
Nur Amin, Sadia; Shivakumara, Palaiahnakote; Xue Jun, Tang; Yang Chong, Kai; Leong Lon Zan, Dillon; Rahavendra, Ramachandra
Authors
Dr Shivakumara Palaiahnakote S.Palaiahnakote@salford.ac.uk
Lecturer
Tang Xue Jun
Kai Yang Chong
Dillon Leong Lon Zan
Ramachandra Rahavendra
Abstract
The food industry is becoming competitive on a daily basis and introducing newer cuisines to the menu in an attempt to rise up the ladder. But they still are not being able to improve their performances because customers often only have the waiters to describe the dishes to them and thus, most of the time results in not fulfilling their expectations. Thus, to allow the customers to visualize their orders more informatively, this paper presents an android application that overlays digital three-dimensional (3D) food models onto a quick responsible (QR) code image marker on a food menu using augmented reality (AR) technology through the camera of the system. Moreover, the price and a detailed list of the ingredients used to prepare the dish, along with the nutritional and calorie content, will also appear beside the 3D food model to keep the customers completely informed of what they will be ordering. This work focused on designing the 3D food models in the Blender 3D tool, which were then imported into the Unity 3D application with the Vuforia software development kit preinstalled, and Figma has been utilized for designing the user interface of the system. The study’s outcome is an AR application that provides the customer with a more engaging approach to visualize the dishes in 3D form, which can improve customer sales and restaurant loyalty.
Citation
Nur Amin, S., Shivakumara, P., Xue Jun, T., Yang Chong, K., Leong Lon Zan, D., & Rahavendra, R. (2022). An Augmented Reality-Based Approach for Designing Interactive Food Menu of Restaurant Using Android. #Journal not on list, https://doi.org/10.47852/bonviewAIA2202354
Journal Article Type | Article |
---|---|
Acceptance Date | Oct 10, 2022 |
Publication Date | Oct 10, 2022 |
Deposit Date | Nov 15, 2024 |
Publicly Available Date | Nov 18, 2024 |
Journal | Artificial Intelligence and Applications |
Peer Reviewed | Peer Reviewed |
DOI | https://doi.org/10.47852/bonviewAIA2202354 |
Files
Published Version
(4.5 Mb)
PDF
Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/
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