Reaug an Implemented Augmented Reality enabled Scanner for Restaurants
Divakar Harekal1, Veena G.S2., Ankit Goyal3, Rahul Sinha4

1Dr. Divakar Harekal, Assistant Professor, Department of CSE, Ramaiah Institute of Technology, Bengaluru, Karnataka India.

2Mrs. Veena G.S., Student Assistant Professor, Department of CSE, Ramaiah Institute of Technology, Bengaluru, Karnataka India.

3Ankit Goyal, Student, Department of CSE, Ramaiah Institute of Technology, Bengaluru, Karnataka India.

4Rahul Sinha, Student Department of CSE, Ramaiah Institute of Technology, Bengaluru, Karnataka India.

Manuscript received on 7 June 2019 | Revised Manuscript received on 12 June 2019 | Manuscript Published on 08 July 2019 | PP: 1-4 | Volume-8 Issue-8S3 June 2019 | Retrieval Number: H10010688S319/19©BEIESP 

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In our research paper with the use of a well-executed augmented reality (AR) marker in which we are using the combined properties of QR code and AR to scan the QR code associated with the particular restaurant menu. Scanning will result in obtaining of 3-D images of all the dishes present in that restaurant along with the dish details like health constituents, servings, how a particular dish tastes like and many more details associated with that dish. In this way we are elevating the dine-in experience by removing the traditional menu ordering process. It is directed at eliminating the discomfort customers are facing due to food and language gaps. Visual representation of food will give unique experience and due to this wide range of customers will prefer to come to restaurants. So overall it will revolutionize the conventional ordering system which is followed in the restaurants.

Keywords: Reaug Overview, Augmented Reality, AI Scanner, Fast Scan AI Techniques.
Scope of the Article: Materials Engineering