Keeping customers moving: The technology helping LNER and Network Rail run an on-time railway

The two rail companies have partnered up to install equipment across the LNER Azuma and InterCity 225 fleets which monitors the condition of the East Coast Main Line and beyond.

Pantograph Damage Assessment System (PANDAS) and Automated Intelligent Video Review (AIVR) constantly assess overhead line equipment (OLE) and track, reports any potential damage, and helps engineers proactively fix any issues before they can lead to severe disruption, which can cost the taxpayer millions of pounds each year and delay customers for hours.

PANDAS was initially fitted to a Class 91 around four years ago. Now, after a wider roll out in 2025, it is on five LNER Azuma units and on four Class 91 locomotives and means the entire electrified East Coast Main Line is covered every day.

The equipment is fitted on the roof of a train, including part of it on the pantograph, and uses artificial intelligence and machine learning to continuously analyse pantograph and overhead line interactions, providing accurate, up to date information to Network Rail engineers.

AIVR was fitted to two bi-mode LNER Azuma units in January 2026, with a view to roll the technology out on more trains. Currently, the equipment allows the vast majority of the near 1,000 mile LNER network to be covered and analysed each week. The system uses underbody cameras which capture line-scanning data, providing engineers with a comprehensive capture of the track.

Gunnar Lindahl, Joint Operations Director, LNER and Network Rail, said: “We want to provide our customers with the best possible journey when they travel by train. We know how frustrating it can be when trains are delayed or cancelled by infrastructure problems, and this technology actively combats that.

“LNER and Network Rail are working more closely than ever, running a safe, reliable railway, connecting millions of customers across the East Coast Main Line and beyond.”

Both systems are already delivering results.

In the last 12 months, PANDAS has driven the removal of 19 overhead line defects that may have otherwise gone unseen. Network Rail engineers believe that these defects could have gone on to cause at least four significant issues with the overhead wires, such as a dewirement, across the network, typically causing over 1,500 Time to 3* failures, over 4,000 minutes of delay, and around 50 full or part cancellations per incident.

This means that, without PANDAS, customers could have faced at least 11 days of delay, potentially causing missed connections and costing the industry thousands of pounds in Delay Repay compensation.

AIVR, too, is helping to keep trains on the move. In January 2026, a track defect was reported by a train driver in Cambridgeshire which caused over 10,000 delay minutes, multiple cancellations, and led to a full day of disruption for customers.

However, a week later, the AIVR system identified a minor fault which had the potential to turn into a larger issue near Retford. The report allowed engineers to carry out an overnight repair, with no delay to passengers, and zero delay minutes caused.

Gunnar continued: “This technology has been invaluable to us. It allows us to be more strategic and deliberate in deploying our engineers and helps us make sure that the areas most in need of attention receive it. Both systems will evolve and develop as we continue to place our focus on delivering reliability for our customers.”