FURI | Summer 2024

Building YMS (Yard Management System) using Machine Learning and Optical Character Recognition Technology

This project addresses the research question: “How can Machine Learning (ML) and Optical Character Recognition (OCR) technologies be effectively leveraged to optimize yard management processes and reduce inefficiencies in logistics operations, particularly in automating the identification and processing of container numbers, vehicle details, and driver information at entry gates?” The project aims to replace the manual yard management system, which leads to errors and congestion during peak periods, with an automated system using CCTV and OCR technologies. This will reduce processing times, minimize gate congestion, and improve operational efficiency and data accuracy. The project also explores the broader implications of these technologies in logistics and transportation, contributing to advancements in data analysis, machine learning education, and the application of AI in real-world scenarios.