The challenges of maintaining railway infrastructure have never been greater nor more critical. Today, many transport companies rely on visual inspections and dedicated fleets of maintenance trains to find out what’s compromising the network.
With aging rail infrastructure under strain and a shortage of skilled maintenance workers, a more efficient method is crucial to manage the extensive network of tracks, overhead lines, and surroundings.
HMAX for Infrastructure from Hitachi Rail uses sensors fitted on existing fleets of passenger and freight trains to bring data about track health, ride quality, overhead lines and vegetation into a single platform.
By using machine learning and AI to monitor and capture the health of railway infrastructure, transport operators can now optimize operating costs while increasing the reliability of the railway ecosystem.
HMAX for Infrastructure
Rail Infrastructure
Following the acquisition of Omnicom Balfour Beatty in 2025, HMAX now offers new train-borne capabilities to monitor rail infrastructure, including mobile monitoring, mobile measurement and remote monitoring.
By integrating camera, lidar systems alongside our vibration monitoring capabilities, HMAX can now use train-borne sensors to capture more accurate rail data more often for greater operational stability.
Overhead Lines
In partnership with NVIDIA, HMAX now uses edge-to-cloud AI computing capabilities to process video of pantograph and overhead lines and identify potential issues. NVIDIA’s technology has enabled unprecedented improvement to real time multi-stream image processing for pantograph cameras on the train, enabling real-time monitoring and detection of issues on the overhead line.
Vegetation Management
HMAX can also observe the natural environment and track, including vegetation and embankments. Monitoring areas in real-time further enhances safety, helping detect potential hazards like overhanging or invasive tree species, leaves on the track, or embankment subsidence that could cause harm or delays.