Hitachi

Solution

Hitachi built a rail-inspection solution on Databricks Lakehouse to turn video captured from train-mounted cameras into near-real-time maintenance intelligence. Video streams covering roughly 40,000 kilometers of overhead lines are uploaded from trains to the cloud and processed on Databricks, where Delta Lake handles storage and pipelines for the large, mixed data volumes. MLflow manages model training, deployment and experiment tracking for the computer-vision workflows that detect defects and line displacement, while Databricks SQL dashboards surface production alerts, model performance and other operational metrics. Shared workspaces and notebooks let data engineers and scientists collaborate on reusable code and models. As fresh video is analyzed, the system generates alerts that dispatch workers to the affected area, giving rail network owners a predictive maintenance workflow that replaces slow manual inspections and reactive outage response.

Data flow

Video from cameras mounted on trains is uploaded to the cloud and processed in Databricks, where Delta Lake stores inspection data and MLflow-managed models analyze frames for overhead-line defects or displacement. Detected issues are surfaced in Databricks SQL dashboards and trigger alerts that send workers to the affected section of track.