JAPAN: Odakyu Electric Railway is testing the use of Nokia’s SpaceTime scene analytics to provide real-time warnings of obstructions at level crossings.
The railway currently uses 137 radar units for object detection on its 120·5 km three-line network with 229 crossing points. The trial will assess whether applying machine-learning to the images being produced by existing level crossing monitoring cameras could offer better performance than radar, with a reduction in downtime and operational costs.
‘Odakyu Electric Railway is renowned for being an early adopter of new technology, and this trial illustrates the role that AI can play in delivering enhanced levels of vigilance’, said John Harrington, Head of Nokia Japan. ‘This is a critical milestone for Nokia to help contribute not only to railway safety improvement but also to decrease operational costs and enhance performance.’
SpaceTime runs on edge computing resources, reducing the bandwidth required at remote sites with limited connectivity.
‘Network-connected cameras are one of the most prolific sources of Internet of Things data that can provide valuable insights to help promote high safety standards’, said Harrington. ‘By running machine learning analytics on camera feeds, and sending solely relevant scenes and events to operators, the full benefits of video surveillance can be realised in a wide variety of settings, with rail crossings a particularly relevant use case.’