Alejandro Valencia-Arias, Sebastián Cardona-Acevedo, Ezequiel Martínez Rojas, Juana Ramírez Dávila, Paula Rodriguez-Correa, Lucia Palacios-Moya, Renata Teodori de la Puente, Erica Agudelo-Ceballos, Martha Benjumea-Arias
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引用次数: 0
Abstract
Background: The automation of processes and services has transformed various industries, including the restaurant sector. Technologies such as the Internet of Things (IoT), machine learning, Radio Frequency Identification (RFID), and big data have been increasingly adopted to enhance service delivery, improve user experiences, and enable data traceability. By collecting user feedback and analyzing sentiments, these technologies facilitate decision-making and offer predictive insights into future food preferences. This study aims to explore current research trends in intelligent restaurants, focusing on technological applications that improve service and decision-making.
Methods: A bibliometric analysis was conducted in accordance with the PRISMA-2020 guidelines. A total of 94 academic documents were reviewed from the Scopus and Web of Science databases, focusing on publications related to intelligent restaurant systems, particularly involving IoT and automation technologies.
Results: The analysis revealed that the United States, India, and China have contributed the most to the field, with a particular emphasis on China's implementation of IoT architecture and robotics in restaurant settings. Chinese restaurant innovations, particularly in robotics, are among the most frequently cited in the literature. The study identifies these countries as leading the research in the intelligent restaurant domain.
Conclusions: Technologies such as IoT, machine learning, RFID, and big data are driving advancements in restaurant automation, enhancing service efficiency and user experience. The United States, India, and China are leading research in this area, with China standing out for its application of robotics and IoT in restaurants. This research provides a foundation for future studies aimed at improving predictive models for food selection and service optimization.
背景:流程和服务的自动化已经改变了许多行业,包括餐饮业。物联网(IoT)、机器学习、射频识别(RFID)和大数据等技术已被越来越多地用于增强服务交付、改善用户体验和实现数据可追溯性。通过收集用户反馈和分析情绪,这些技术有助于决策,并提供对未来食物偏好的预测性见解。本研究旨在探讨目前智能餐厅的研究趋势,重点关注提高服务和决策的技术应用。方法:按照PRISMA-2020指南进行文献计量学分析。共审查了来自Scopus和Web of Science数据库的94篇学术论文,重点是与智能餐厅系统相关的出版物,特别是涉及物联网和自动化技术的出版物。结果:分析显示,美国、印度和中国对该领域的贡献最大,特别强调了中国在餐厅环境中实施物联网架构和机器人技术。中国餐馆的创新,尤其是机器人技术,是文献中最常被引用的创新之一。该研究指出,这些国家在智能餐厅领域的研究处于领先地位。结论:物联网、机器学习、RFID和大数据等技术正在推动餐厅自动化的进步,提高服务效率和用户体验。美国、印度和中国在这一领域的研究处于领先地位,中国在机器人和物联网在餐馆的应用方面表现突出。该研究为进一步完善食品选择和服务优化的预测模型奠定了基础。
F1000ResearchPharmacology, Toxicology and Pharmaceutics-Pharmacology, Toxicology and Pharmaceutics (all)
CiteScore
5.00
自引率
0.00%
发文量
1646
审稿时长
1 weeks
期刊介绍:
F1000Research publishes articles and other research outputs reporting basic scientific, scholarly, translational and clinical research across the physical and life sciences, engineering, medicine, social sciences and humanities. F1000Research is a scholarly publication platform set up for the scientific, scholarly and medical research community; each article has at least one author who is a qualified researcher, scholar or clinician actively working in their speciality and who has made a key contribution to the article. Articles must be original (not duplications). All research is suitable irrespective of the perceived level of interest or novelty; we welcome confirmatory and negative results, as well as null studies. F1000Research publishes different type of research, including clinical trials, systematic reviews, software tools, method articles, and many others. Reviews and Opinion articles providing a balanced and comprehensive overview of the latest discoveries in a particular field, or presenting a personal perspective on recent developments, are also welcome. See the full list of article types we accept for more information.