Minister of Transport and Infrastructure Uraloğlu stated that artificial intelligence can predict potential malfunctions in automatic train inspection stations. Minister of Transport and Infrastructure Abdulkadir Uraloğlu emphasized the integration of Artificial Intelligence with the Automatic Train Inspection Station (ATIS) system, stating that “Artificial intelligence algorithms at automatic train inspection stations evaluate collected big data to detect possible malfunctions before they occur and send early warnings to maintenance teams for preventive interventions.” Uraloğlu highlighted in a written statement that the Republic of Turkey State Railways (TCDD) has undergone a significant transformation in railway transportation with investments in digitalization and AI-based technologies. Mentioning the acceleration of AI integration with native solutions to make Turkey’s railway network compatible with the digital age, Uraloğlu expressed that the ATIS System developed in collaboration between TCDD and TÜBİTAK was integrated with artificial intelligence. Uraloğlu indicated that thanks to this system, while trains are in motion, all critical components can be analyzed, saying, “Equipped with AI-based image processing and sensor systems, this system scans each part of the train in detail to generate real-time data.”

“MAXIMIZING SERVICE CONTINUITY”
By using this technology, Uraloğlu pointed out that wheel abrasions, errors in brake discs, axle bearing temperatures, load imbalances, and other mechanical components are analyzed in real-time. He said, “Artificial intelligence algorithms at automatic train inspection stations detect possible malfunctions before they occur by evaluating collected big data and send early warnings to maintenance teams for preventive interventions. Unforeseen malfunctions are prevented, maintenance costs are reduced, and train service continuity is maximized. Additionally, by offering remote monitoring and analysis across railway lines in Turkey, we significantly improve maintenance processes.” Bakan Uraloğlu mentioned the widespread use of “predictive” maintenance systems for continuous monitoring of railway infrastructure and more efficient management of maintenance processes, ensuring that railway vehicles equipped with special sensors enable intervention before malfunctions occur, consequently increasing operational continuity while significantly decreasing costs. Stressing that safety is a top priority in railway transportation, Uraloğlu stated that AI-based analysis systems track the facial expressions, eyelid closure times, and head positions of the train conductors to detect distraction and provide warnings when needed.

“MAXIMIZING EFFICIENCY WITH THE LOWEST ENERGY CONSUMPTION”
Uraloğlu emphasized that the Eryaman Monitoring Center continuously monitors high-speed train (YHT) lines, mentioning, “In this center, critical infrastructures such as tunnels, bridges, culverts, and viaducts are monitored 24/7 via smart cameras and sensors. At the same time, when any negative situation is detected remotely on the lines, the relevant teams are promptly informed, minimizing intervention times. The condition of structures such as bridges, culverts, and tunnels in railway infrastructure is continuously analyzed, optimizing the maintenance processes through early warning systems.” Uraloğlu predicted that autonomous trains and AI-based signalization systems would become more widespread in the coming years. He stated, “Through AI-supported energy management systems, our trains will achieve maximum efficiency with the lowest energy consumption. This will reduce carbon emissions and lower operational costs. Smart assistants and chatbots will analyze passengers’ needs to offer the most convenient travel plans. Passenger comfort will be significantly enhanced with digitization.”