APPLYING YOLO OBJECT DETECTION SYSTEM TO IMPROVE THE CASHIER SYSTEM

• Main Author: Rohman Muhammad, Faiz
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/83853
• Institution: Institut Teknologi Bandung

In this study, we present an different approach to enhance current barcode systems by integrating You Only Look Once (YOLO) object detection with current sale systems. The methodology involves the development of a sophisticated AI model capable of recognizing various products commonly sold in retail environments. This model feeds directly into a custom program designed to match detected objects with their corresponding prices, thereby automating the checkout process. The resulting system serves as a proof of concept, demonstrating the feasibility of using advanced object detection techniques to streamline and potentially revolutionize retail transactions. The findings indicate that while the system is effective in its current iteration, there is substantial potential for future improvements to increase accuracy and expand the range of detectable items. This research paves the way for further advancements in automated retail solutions, highlighting the practical applications of YOLO in enhancing efficiency and accuracy in sales operations.