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Nokia and Schweizer Electronics deploy AI-based video analytics to improve railroad safety

Nokia and Schweizer Electronics deploy AI-based video analytics to improve railroad safety

SoftwareSwitzerlandTop StoriesTransport

Nokia has announced the deployment of its Scene Analytics solution for Baselland Transport AG (BLT) in Münchenstein, Switzerland. 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.

The safety of passengers and vehicles at level crossings remains a concern for rail authorities due to the threat of serious injury or loss of life in these areas. Statistics from the European Union identified around 250 fatalities and 300 serious injuries related to level crossings in the EU-28 countries in 2018. Even the best warning systems can be bypassed and crossings obstructed, making it essential for train operators to be alerted of issues in real-time.

Roland Liem, Head of Product Unit Railroad Safety at Schweizer Electronics, said:“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. This will enable rail operators to close barriers and respond to dangerous situations at crossings in real-time.”

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.

Besides improving safety and response time, the deployment of Scene Analytics on railroad crossings also increases operational efficiencies by minimising 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 (RoI).

Michael Theiler, Head of Maintenance Electrical Systems at BLT, said:“Level crossings are notoriously difficult areas to ensure the safety of passengers, pedestrians, train operators and motorists. 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.”

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