As the first deployment of this kind in Europe, Nokia’s collaboration with Schweizer Electronics and BLT demonstrated the reliability of AI-based railroad safety solutions for daily use. - Photo: Nokia

As the first deployment of this kind in Europe, Nokia’s collaboration with Schweizer Electronics and BLT demonstrated the reliability of AI-based railroad safety solutions for daily use.

Photo: Nokia

Nokia announced the deployment of its Scene Analytics solution for Baselland Transport AG (BLT) in Münchenstein, Switzerland, according to the company's press release.

The AI-based system applies computer vision and machine learning technologies for real-time monitoring and analysis, to ensure the safety of railroad crossings. As the first deployment of this kind in Europe, Nokia’s collaboration with Schweizer Electronics and BLT demonstrated the reliability of AI-based railroad safety solutions for daily use.

Statistics from the European Union identified around 250 fatalities and 300 serious injuries related to level crossings in the EU-28 countries in 2018[1].

Integrating Nokia Scene Analytics, BLT can use machine learning algorithms based on CCTV data to continually learn what is “normal” or anomalous.

In addition to reporting anomalies to railway security in real-time, the AI-based platform detects the object type, which provides a more complete picture of the situation at hand. Event based video clips, images, and associated data are stored, enabling post-incident forensic analysis.

“Level crossings are notoriously difficult areas to ensure the safety of passengers, pedestrians, train operators, and motorists," said Michael Theiler, Head of Maintenance Electrical Systems at BLT. "This deployment, in collaboration with Nokia represents an encouraging step towards using analytics as another layer of protection in dangerous areas. Nokia Scene Analytics acts as an intelligent set of ‘eyes’ and, by providing critical information in real-time, to prevent or mitigate the impact of an incident."

Besides improving safety and response time, the deployment of Scene Analytics on railroad crossings also increases operational efficiencies by minimizing downtime and delays. Its machine learning capability reduces the time investment required by rail personnel to manually update the system. In doing so, Nokia Scene Analytics provides train operators with much greater overall cost efficiency. It can also be integrated with many standard industry cameras, reducing the total cost of ownership, and increasing the return on investment.

“By combining level crossing systems and Scene Analytics within a simple interface, this project with Nokia and BLT enabled us to automate the interaction between level crossing systems and alarms for enhanced safety," said Roland Liem, Head of Product Unit Railroad Safety at Schweizer Electronics. "This will enable rail operators to close barriers and respond to dangerous situations at crossings in real-time.”

0 Comments