Smart Dining: A QR Code-Based Restaurant System with Real-Time Order and Kitchen Monitoring for Archangel Cuisine
by Balanday, Shane, B., Cansino, John Michael, Coronel, Rashied, G., Fababier, Carlos, Gabiosa, Polo Justine, S., Raymundo, Carl Andrei, A., Viloria, Jhonsen, A., Yu, Mikaella Marie, P., Zubiaga, Justine
Published: July 6, 2026 • DOI: 10.51584/IJRIAS.2026.11060168
Abstract
This study aims to develop a QR code-based restaurant management system with integrated order tracking and kitchen monitoring for Archangel Cuisine. It seeks to replace the existing manual ordering process with a digital platform that allows customers to place and monitor their orders in real time. The study also intends to determine how the system can improve order accuracy, service efficiency, and customer satisfaction. Lastly, it aims to evaluate how the system can contribute to modernizing local restaurant practices and serve as a model for similar establishments.
This study employed a mixed-methods research design, combining both quantitative and qualitative approaches to provide a comprehensive evaluation of the proposed QR Code-Based Restaurant Management System. The use of a mixed-methods design was appropriate because the study examined both measurable system performance, such as order accuracy, processing time, workflow efficiency, and user satisfaction ratings, as well as human experiences, including customer perceptions, staff feedback, and usability observations. Quantitative data provided objective evidence of the system’s effectiveness, while qualitative data offered deeper insights into users’ experiences and perceptions.
Furthermore, the research questions required both forms of data, as system efficiency and order accuracy were best measured quantitatively, whereas user experiences and perceptions were better explored through qualitative methods. The integration of both approaches also enabled triangulation, allowing findings from surveys, interviews, and observations to validate and support one another.
This system will provide an efficient platform for customers to place orders, track their food in real time, and interact digitally with the restaurant. It also aims to assist kitchen staff in monitoring orders systematically, reducing errors, and improving overall workflow efficiency.