Woon, Co Ying (2025) Visionserve: A vision based food detection system for fast food restaurants. Final Year Project, UTAR.
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Abstract
This project explores the development of a vision-based food detection system using advanced computer vision and image recognition techniques, optimized for use in fast-food restaurants in Malaysia. The goal of this system is to automate the detection of food items, thereby enhancing operational efficiency, minimizing human error, and improving overall customer satisfaction. The driving force behind the project is the real challenges faced daily in McDonald’s restaurants, where rapid and efficient service is critical. Customers often receive wrong items, which leads to frustration and long queues at the counter. Staff also spend time re-checking orders repeatedly, slowing down operations and increasing the risk of mistakes. During peak hours and promotional events, when restaurants are crowded, these issues become even more pressing, placing additional stress on staff and customers alike. Mistakes made in identification and distribution of food items can cause complaints from customers and potential loss of business for restaurateurs. This technology is thus presented as an adjunct technology solution, not as a replacement for humans, but as an intelligent tool that supports and supplements human force and enhances fast food restaurant’s universal service platform. The system utilizes computer vision methods trained to recognize various fast-food items such as burgers, fries, and drinks. When recognized, the system summarizes recognized food items on the tray. Deliverables under the project involve creating and launching an operational prototype, verifying its performance on the ground level on the terms of simulation within a fast-food restaurant condition, and total technical documentation for any potential commercial deployment or further works. Lastly, but significantly, this vision-based food detection system is one of the pacesetters of Malaysian fast-food operations in modernization. It improves service dependability, accommodates workforce diversity, and positions fast-food restaurant chain as a leader in embracing artificial intelligence and intelligent automation technology in the quick-service restaurant sector.
| Item Type: | Final Year Project / Dissertation / Thesis (Final Year Project) |
|---|---|
| Subjects: | T Technology > T Technology (General) T Technology > TD Environmental technology. Sanitary engineering |
| Divisions: | Faculty of Information and Communication Technology > Bachelor of Computer Science (Honours) |
| Depositing User: | ML Main Library |
| Date Deposited: | 29 Dec 2025 18:19 |
| Last Modified: | 29 Dec 2025 18:19 |
| URI: | http://eprints.utar.edu.my/id/eprint/7247 |
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