Artificial intelligence software is helping Network Rail find and remove forgotten debris from the trackside faster and safer than ever before..
The Network Rail Southern region trialed One Big Circle’s video and AI technology to find old railroad kits that can be reused or recycled, reduce the risk of colleague injury from slips, trips and falls, and organize railroads. Leading. at the same time.
The technology, known as Automated Intelligent Video Review (AIVR), captures high-definition train point-of-view video from across the rail network, which can be instantly accessed in the cloud.
This footage is analyzed by AI to detect abandoned rails, sleepers and ballast bags and map their locations using GPS so maintenance teams can plan when and how to safely remove items. You will be able to
Wayne Cherry, senior innovation engineer at Network Rail, said: “Technologies such as AIVR offer Network Rail a great opportunity to improve its efficiency as a business.
“Although AIVR has already been used in other parts of Network Rail, this is the first time the technology has been used in AI in this way and has the potential to be truly transformative.
“Scrap on the side of the railroad is not only unsightly, but also interferes with planned earthwork, blocks safe passage, and delays teams accessing parts of the railroad infrastructure for repairs during disruptions. There is a possibility.
“If we can identify and remove waste materials more safely and efficiently, we will not only ensure the safety of our colleagues, but also benefit the broader rail industry, passengers and taxpayers.”
The project is currently being trialled on the Wessex route, one of the busiest on the rail network, through all or parts of the counties of Surrey, Berkshire, Hampshire, Dorset, Devon, Somerset and Wiltshire, before considering commencement. out wider.
This new technology not only helps improve efficiency, but also has safety and economic benefits.
“Slips, trips and falls” are the leading cause of injury on Network Rail’s Wessex lines, and trackside scrap is a significant hazard, especially since most of the work is done in the dark.
Network Rail’s Safety and Health Advisor for Wessex Lines, Martin Shaftow, who is leading the project, said: “We are delighted to be working with One Big Circle on this exciting project. I believe it will play a vital role in improving the overall condition of the railway for the benefit of passengers and the local community.
“Unfortunately, in recent years, railroads have become dumping grounds for discarded sleepers, scrap rails, surplus ballast bags and many other assets. There is no clear list of where the assets are located.
“The possibility of using high-definition video footage and AI to pinpoint the location of waste materials without my colleagues having to walk along the tracks presents a huge opportunity to improve safety.”
Financially, not only can some of the scrap material be recycled and the money generated can be used to support railroad operations, but some of the leftover material can also be reused. For example, Bomac concrete sleepers are no longer manufactured, but are still in demand as a replacement for sidings and some railroad tracks. Thanks to this technology, 40 of these sleepers have been identified at a site between Yeovil and Weymouth where they can be collected and stored for future use throughout the operation, eliminating the need to purchase expensive new equivalents. disappears.
Mr Martin added: “It is an exciting prospect to contribute to the potential cost savings for the industry by reusing or recycling this treasure trove of scrap materials, and we look forward to rolling it out even more broadly across our business, hopefully later this year.”
Emily Kent, co-founder and director of One Big Circle, said: “This is a very exciting AI application developed in collaboration with Network Rail experts.
“The AIVR system collects high-quality wayside imagery from across the UK and helps a wide variety of engineers and disciplines see what they need to see without being onsite.
“By adding more intelligence to that data, we are able to automatically detect and locate abandoned rails and other hazards along the track, allowing us to focus on specific issues and respond quickly and safely. increase.”
Photo credit: Network Rail
