Your browser doesn't support javascript.
Arduino Based Restaurant Menu Ordering System
Acta Marisiensis Seria Technologica ; 20(1):43-48, 2023.
Article in English | Academic Search Complete | ID: covidwho-20231707
ABSTRACT
The role of restaurants, canteens, other forms of eatery and food service outlets are becoming very big part of most economies at different levels. However improvement in customer experience while making orders plays a very critical role in having a smooth and efficient menu ordering process. This article presents a novel hybrid approach that tackles the challenges associated with menu ordering especially in the post-covid era;both from software and hardware perspectives. First, a web-application - powered by ReactJS and GraphQL, which enables order request anywhere at any time was developed. In addition, is the implementation of hardware with mobility feature on trips to the restaurant using two Arduino microcontrollers (transmitter and receiver). The result allows the user to browse through a catalogue, check-in and out on a Thin-Film-Transistor (TFT) liquid-crystal display (LCD) and deliver a seamless experience to the customer. [ FROM AUTHOR] Copyright of Acta Marisiensis. Seria Technologica. is the property of Sciendo and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
Keywords

Full text: Available Collection: Databases of international organizations Database: Academic Search Complete Topics: Long Covid Language: English Journal: Acta Marisiensis Seria Technologica Year: 2023 Document Type: Article

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: Databases of international organizations Database: Academic Search Complete Topics: Long Covid Language: English Journal: Acta Marisiensis Seria Technologica Year: 2023 Document Type: Article