A state-of-the-art trial using AI-enhanced CCTV aims to improve safety on the East Coast Main Line.
- The initiative, started in May 2024, involves a forward-facing CCTV camera installed in an LNER Azuma.
- Hitachi Rail and CrossTech are collaborating to automate the detection of vegetation and landslips.
- Network Rail highlights the financial impact of vegetation-related incidents costing millions annually.
- The trial aims to offer insights for optimising maintenance and minimising disruption.
The East Coast Main Line is currently at the forefront of technological innovation with a trial involving the use of artificial intelligence-powered forward-facing CCTV cameras. Beginning in May 2024, a camera was installed in the driver’s compartment of an LNER Azuma train. This initiative, led by Hitachi Rail in partnership with British SME CrossTech, aims to provide real-time automated detection of overhanging trees, leaves, and landslips.
The trial is described by Hitachi Rail as pivotal in digitising infrastructure monitoring and maintenance. Utilising cutting-edge AI camera sensor technology, the system not only detects potential hazards such as intrusive tree species and subsidence but intends to significantly enhance railway safety. The implications of real-time monitoring include the proactive prevention of incidents that could jeopardise train operations or result in delays.
Network Rail, addressing the financial consequences of such hazards, reports that vegetation-related incidents could cost up to £3 million annually in the Southern region alone. Automating the identification process of these potential threats promises to yield valuable insights into infrastructure maintenance strategies. Hitachi Rail affirms that the trial will provide valuable guidance for optimising the East Coast Main Line’s maintenance.
The collaborative effort with CrossTech is hailed as an example of digital innovation. Hitachi Rail supports the integration and operational functionality using its digital expertise, reflecting a synergy between the global rail leader and local SME innovation. Network Rail’s engineer Johanna Priestley emphasises the initiative’s capacity to offer driver-perspective footage, aiding in the understanding of how vegetation may impact train operations or visibility.
Additional support comes from LNER Engineering Director Linda Wain, who notes the significance of real-time updates provided by the technology fitted within train cabs. CrossTech’s managing director, Haydon Bartlett-Tasker, expresses enthusiasm for introducing advanced computer vision analytics to the rail infrastructure. This collaboration is viewed as a testament to enduring partnerships with Network Rail’s regional sectors, fostering a safer railway environment.
This innovative trial represents a significant advancement in using AI for infrastructure maintenance and safety enhancement on the railway network.
