2025

Pitkäkangas, Ville; Kaakinen, Heikki; Tuunainen, Tom; Isohanni, Olli; Jose, Mitha Rachel

Computer vision has emerged as a game-changing technology in the mining industry, revolutionizing operations and unlocking various use case scenarios. With increased trade facilities, ports are recognized as one of the most diligent work environments globally. The applications of machine learning and computer vision in ports offer improved security, efficient container management, intelligent traffic management, predictive maintenance, automated operations, and environmental monitoring. These advancements contribute to streamlined processes, cost reduction, enhanced safety, and overall optimization in port environments. This study proposes an approach to detect and classify vehicles in a port during the wintertime in Finland using computer vision and machine learning methods. Due to the high variability between seasons, particularly winter and summer in Finland, there might be a need to categorize images by time of year. The study is developed as a model to detect and classify vehicles in the port area, and the port used in the study acts as an international hub for various trades and industries, including but not limited to chemistry and mining.