Rail Vision

Modernize railcar maintenance 

This solution employs cameras for image capture which are used for detection and classification of defects. Employing a dual-phase methodology, it first utilizes neural networks to categorize images of railcars into distinct types, subsequently identifying any structural flaws present. The imagery is captured by strategically positioned cameras within rail yards. 

Neural network classification 

 Accurately categorize railcar images, facilitating precise defect identification and streamlined analysis. 

Structural flaw detection

Detect and flag structural flaws swiftly and reliably, enabling proactive maintenance interventions. 

Predictive maintenance scheduling 

Optimize maintenance planning and leverage historical data and condition monitoring to anticipate maintenance requirements and minimize downtime.

Real-time monitoring dashboard 

Provide instant visibility into railcar conditions and enable prompt decision-making for maintenance and operational needs.  

XR Maintenance

Enables hands-free, voice-controlled inspections, enhancing safety and efficiency with step-by-step guidance and quick report generation, optimizing vehicle acceptance rates.

View solution

KM Monitor

Tracks coach distance using advanced firmware, data optimizations, and NB-IoT monitoring, ensuring seamless lifecycle support from provisioning to analytics dashboards.

View solution

Staff Companion

Simplifies staff tasks at stations, in trains, and in buses. It integrates voice-to-text capabilities for hands-free convenience, offers comprehensive onboarding FAQs and smoother operations.

View solution