One of the long-term research topics of the research team from the Institute of Automation and Computer Science has been development of SMART technologies for railway applications. The aim of these technologies is to provide key information about the operational status of infrastructure and trains, and to utilize this information for predictive maintenance. Early detection of faults and defects in infrastructure components, foreign objects falling on the track, or failures of critical infrastructure elements that could lead to potential train derailments, is crucial for ensuring the safety and reliability of railway operation and for long-term reduction of operational and maintenance costs.

This is achieved through the use of SMART sensing systems that can autonomously record and transmit data wirelessly to the cloud where they are processed and evaluated to provide feedback for track operators. The development process of these systems is based on a multidisciplinary approach requiring the implementation of computational models and digital twins of the infrastructure systems and its components, cyber-physical systems for data collection, and advanced artificial intelligence methods for data evaluation and predictive maintenance of critical systems.

Research in this area is driven by industry needs and is conducted in close collaboration with leading domestic companies, including manufacturers of railway infrastructure components, safety and signalling systems, and local and regional railway infrastructure operators in the Czech Republic. As part of international cooperation, a similar system has been successfully deployed in Taiwan.

Media
https://www.idnes.cz/brno/zpravy/vyvoj-senzory-zeleznice-koleje-doprava-odhaleni-rizika.A230413_112502_brno-zpravy_mos1 (in Czech)

Contact
Ing. Filip Kšica, Ph.D.