Case File2024
Digital Twin-Based Desert Environment Monitoring for Rail Tracks
NYU Abu Dhabi · SMART Lab with Etihad Rail
Proposed and field-piloted a train-mounted sensing concept for Etihad Rail: LiDAR, cameras, and supporting sensors capture the rail corridor so the surrounding geo-environment can be reconstructed in 3D. The aim is early detection of desert-environment hazards that threaten operations — sand movement, water accumulation, and vegetation encroachment — giving maintenance teams a proactive view of track-side risk across UAE conditions.
System Record
- Application
- APPRail Transport
- Environment
- Platforms
- Period
- 2024
My Contribution
Supported the Etihad Rail proposal and train-side sensing pilot — coordinating the industry engagement and the field installation of the rearward LiDAR and camera payload used to capture corridor evidence for the desert-environment monitoring concept.
Development & Validation
- Addresses Middle Eastern rail hazards that cab visibility alone cannot cover: sand dune shifts, flood-related water pooling, and vegetation growth along the alignment.
- Pilot sensor suite mounts LiDAR and cameras on selected trains to collect corridor data and regenerate a dynamic 3D view of the track-side geo-environment for visual monitoring and change detection.
- Machine-learning analysis of environmental change patterns is intended to surface actionable alerts for operators and maintenance teams, supporting safer, more reliable service with fewer weather- and terrain-driven delays.
- Scale path: expand onboard sensing across the fleet into a centralized platform that aggregates train and environmental feeds for network-wide risk awareness and maintenance planning.
Credits & Collaborators
Etihad Rail
Industry partner
Borja García de Soto
NYU Abu Dhabi · SMART Lab
Principal Investigator
SMART Lab
NYU Abu Dhabi
Research partner
Evidence
photograph
Train-mounted LiDAR and camera payload on an Etihad Rail locomotive
video