Case Study: Network Rail reduces maintenance costs and improves rail safety with Faculty's vegetation detection solution

Network Rail detects vegetation encroachment with 95% accuracy using Faculty

Network Rail faced the challenge of maintaining over 20,000 miles of rail track, a time-intensive and costly process. They needed a better way to assess their infrastructure and understand potential network disruption to optimize maintenance schedules and ensure passenger safety. To address this, they worked with Faculty to implement a data science solution.

Faculty built a lineside vegetation encroachment detection tool using geospatial analytics, video footage, 3D reconstruction, and distance measurements. The solution identifies structures and vegetation, measuring track geometry and location to evaluate clearance. This project for Network Rail achieved 95% accuracy in detecting foliage and significantly reduced the cost of unnecessary maintenance, supporting their Digital Railway transformation programme.

Network Rail