Štěpán Rychlý, a student from the Department of Computer Science at the Faculty of Electrical Engineering and Computer Science, won the Škoda Group technical challenge held as part of RailDays 2026. The competition focused on the use of modern technologies in assessing the technical condition of railway vehicles and connected the fields of transport, artificial intelligence and computer vision.
The task was to design an algorithm capable of automatically estimating the wear of carbon strips from camera images of a pantograph. These strips are among the pantograph components that are in direct contact with the overhead line, making their condition important for the safe and efficient operation of railway vehicles.
The solution prepared by Štěpán Rychlý as a one-member team uses methods of artificial intelligence and computer vision. The algorithm first identifies and segments the individual carbon strips in the image, then analyses their shape and thickness and, based on the data obtained, determines the level of wear. The output is an automatically generated ranking of the strips from the least to the most worn.
The proposed approach represents a practical example of the use of computer science in predictive maintenance. Automated image data evaluation can contribute to more efficient planning of service interventions, early identification of risky wear and reduction of failures in railway vehicle operation.
The success of VSB–TUO students was further complemented by second place, achieved by Kateřina Kolaříková, a graduate of the Department of Computer Science, together with Ondřej Ryška, a doctoral student at the Faculty of Safety Engineering. The results of the competition demonstrate the ability of students to apply knowledge from artificial intelligence, image analysis and algorithm design to specific technical tasks from practice.
The Department of Computer Science has long been developing education and professional activities in the areas of artificial intelligence, software development and data analysis. The success in the Škoda Group technical challenge shows that these competences have direct application in industrial and transport-related contexts.