• Version
• Download 31
• File Size 313.55 KB
• File Count 1
• Create Date 18 April 2025
• Last Updated 18 April 2025

Development of Web-Based Multi-Restaurant Management System

Authors:

Madhuri Borawake1, Shruti Bhosale2, Siddhesh Ghare3, Vaibhav Khose4, Aarti Wamane⁵

^1,2,3,4,5Department of Computer Engineering,

Pune District Education Association’s College of Engineering, Manjari Bk., Hadapsar, Pune, Maharashtra, India – 412307

Abstract - This research presents the design and development of a full-featured Multi-Restaurant Management Web Application aimed at revolutionizing how restaurants and users interact in a digital ecosystem. With the increasing demand for digital dining solutions and the growing popularity of food delivery and smart dining systems, our system offers a one-stop solution that bridges the gap between physical restaurant services and online convenience. Built using the MERN stack— MongoDB, Express.js, React.js, and Node.js—the platform offers a robust, scalable, and modular architecture. The application allows users to register, browse through multiple restaurants, view dynamic menus with real-time pricing, and either place online orders or opt for dine-in reservations. Each restaurant, once registered through a secure authentication process, gains access to an extensive suite of tools for managing their day-to-day operations. This includes CRUD functionality for menu and pricing updates, staff and table management, order tracking, and integrated parking slot systems. Furthermore, the platform includes secure payment systems, real-time notifications, and personalized user dashboards. This paper elaborates on the platform’s architecture, implementation methodologies, database design, core functionalities, testing strategies, and deployment infrastructure. Through agile development practices and cloud-based deployment, the system provides a modern and practical solution to the complex requirements of running multi-restaurant services digitally. It stands as a scalable and extensible base for future enhancements such as AI-driven recommendations, loyalty systems, and advanced analytics.

Keywords: Multi-restaurant system, MERN stack, dining system, restaurant management, online ordering, CRUD operations, web application.

Download