This project is a restaurant operations web application built for Mai Shan Yun, designed to streamline everyday restaurant tasks within a single, unified system. The platform manages menus, orders, inventory, payments, tables, and custom food specifications while supporting both front-of-house and kitchen workflows. Each table is assigned a unique QR code linked to its table number; customers scan the code to access the full menu, customize each item by selecting size, preferences, and special accommodations, and place their order directly from their device. Payment is completed within the system, including tax and an optional custom tip. Once an order is submitted, the kitchen receives a printed receipt organized by drinks, appetizers, entrees, and desserts, with all customer-specific instructions clearly listed. On the management side, inventory levels are manually uploaded and automatically updated as orders are placed, allowing managers to maintain accurate, real-time tracking of ingredients and menu items. Overall, the system improves efficiency, reduces errors, and creates a smoother experience for customers, kitchen staff, and management.
What inspired us to create this project was the opportunity to work on a unique prompt that directly impacts a local business in College Station. To better understand the problem and gain firsthand experience, we visited the restaurant, ordered specialty drinks and an appetizer, steamed pork dumplings, to familiarize ourselves with the existing system. This hands-on approach allowed us to observe how the restaurant currently operates and identify areas where the process could be improved.
We built this system by first identifying the main problems in the existing restaurant workflow and then designing solutions to make the process more efficient. We began by organizing the entire menu, including customized options and pricing, using Excel and documentation tools before transferring the data into a MongoDB database. Using JavaScript and React, we developed a user-friendly interface that allows customers to select items, customize their orders, and pay directly from their phones. Each table is assigned a unique QR code to ensure orders are clearly linked to the correct table, preventing confusion when food and drinks are delivered. The MongoDB database serves as the core of the backend, connecting the frontend and enabling customers, kitchen staff, and management to operate seamlessly within a single, unified system.
Some challenges we encountered included the size of our team and our experience levels. We worked as a two-man team, with one member attending their first hackathon and the other attending their second. This limited team size meant we had to balance learning new technologies while building a functional system under time constraints. One of the main technical challenges was connecting the frontend to the backend, which led to multiple errors and required extensive debugging.
We are proud of creating a meaningful project that we can both stand behind. We are especially proud of successfully debugging the system, connecting the frontend and backend, and completing the project as a two-person team, one of whom participated in their first-ever hackathon. This experience taught us resilience and strong time management skills. Working under constant time pressure pushed us to perform beyond our expectations and showed us how important a strong work ethic truly is. Most importantly, we learned how to persevere through long debugging sessions and challenges without giving up.
What’s next for Streamlined Mai Shan Yun is the development of a more advanced inventory system and deeper feature integration. Future improvements include fully integrated payment processing, support for multiple languages, and exporting detailed sales data such as wait times, most popular items, and least popular items. The most important next step is moving toward real-world implementation, with the goal of deploying the system directly within the restaurant to improve daily operations.
Log in or sign up for Devpost to join the conversation.