Valencia-Arias Alejandro, Cardona-Acevedo Sebastián, Martínez Rojas Ezequiel, Ramírez Dávila Juana, Rodriguez-Correa Paula, Palacios-Moya Lucia, Teodori de la Puente Renata, Agudelo-Ceballos Erica, Benjumea-Arias Martha
School of Industrial Engineering, Universidad Senor de Sipan, Chiclayo, Lambayeque, 14001, Peru.
Centro de Investigaciones Escolme-CIES, Institución Universitaria Escolme, Medellín, 050005, Colombia.
F1000Res. 2025 Jun 10;13:1505. doi: 10.12688/f1000research.158066.3. eCollection 2024.
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.
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.
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.
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.
流程和服务的自动化已经改变了包括餐饮行业在内的各个行业。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采用，以提高服务质量、改善用户体验并实现数据可追溯性。通过收集用户反馈和分析情绪，这些技术有助于决策制定，并对未来的食物偏好提供预测性见解。本研究旨在探讨智能餐厅的当前研究趋势，重点关注改善服务和决策的技术应用。
根据PRISMA - 2020指南进行文献计量分析。从Scopus和Web of Science数据库中总共审查了94篇学术文献，重点关注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文献。
分析表明，美国、印度和中国对该领域的贡献最大，特别强调中国在餐厅环境中物联网架构和机器人技术的应用。中国的餐厅创新，尤其是机器人技术方面的创新，是文献中引用频率最高的。该研究将这些国家确定为智能餐厅领域研究的领先者。
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处于领先研究地位，中国在餐厅中机器人技术和物联网的应用方面表现突出。这项研究为未来旨在改进食物选择预测模型和服务优化的研究奠定了基础。
