Automated System for Restaurant Services

Author:

Deksne Liva1,Kempelis Arturs1,Sniedzins Toms1,Kozlovskis Armands1

Affiliation:

1. Riga Technical University, Riga, Latvia

Abstract

The study proposes a smart restaurant system and analyses its benefits to be able to determine system potential advantages in restaurants. Service time is one of the main criteria that can be improved to enhance the speed of the customer service as well as to increase the number of restaurant visitors. To develop the system, solutions found in scientific literature, software and their different architectures are analysed. It has been found out that it is possible to decrease the average restaurant service load time by 52.76 %. Two hypotheses have been proposed for further research in order to determine how a smart restaurant service system can increase chef’s efficiency and how the use of different algorithms can decrease chef’s workload during peak hours.

Publisher

Riga Technical University

Subject

General Medicine

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Implications of Virtual Reality on Environmental Sustainability in Restaurants based on AI;2024 10th International Conference on Communication and Signal Processing (ICCSP);2024-04-12

2. Design and Implementation of a Smart Restaurant Menu Ordering System Using a WiFi Module and RFID Technology;2024 International Conference on Science, Engineering and Business for Driving Sustainable Development Goals (SEB4SDG);2024-04-02

3. User Flexible Approach for Autonomous Restaurant Menu Ordering System;2023 8th International Conference on Communication and Electronics Systems (ICCES);2023-06-01

4. Implementation of Machine Learning based Approach in IoT Network Prototype;2021 IEEE 9th Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE);2021-11-25

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3