Databases and banks of rolling stock and its components
Digitalization of the rolling stock life cycle management.
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Enhancing the accuracy of strategic and operational planning.
Assessment of current performance characteristics and forecasting of critical operating conditions, taking into account real-world operational factors.
Development of computer vision systems for a wide range of applications, using image segmentation, motion detection, and object tracking.
Development of digital twins, predictive equipment monitoring, process optimization and automation.
Conducting mathematical modeling of train dynamics, including the assessment of longitudinal dynamic forces, using in-house software.
Reducing the costs of operating automated systems through the standardization of primary data requirements.
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