Video Analysis Based on Artificial Intelligence to Improve the Safety of Railway Crossing

Nokia announced the deployment of its scenario analysis solution for Baselland Transport AG (BLT) in Mingenstein, Switzerland.

The system based on artificial intelligence applies computer vision and machine learning technology for real-time monitoring and analysis to ensure the safety of railway crossings. Nokia’s cooperation with Schweizer Electronics and BLT demonstrates the reliability of AI-based railway security solutions in daily use.

Due to the threat of serious injury or loss of life in these areas, railway authorities remain concerned about the safety of passengers and vehicles at level crossings. Statistics from the European Union show that about 250 people were killed and 300 seriously injured at level crossings in 28 EU countries in 2018. Even the best warning system can be bypassed and the crossing is blocked, so train operators must be alerted to the problem of level crossings. Instantly.

By integrating Nokia scenario analysis, BLT can use machine learning algorithms based on CCTV data to constantly understand what is “normal” or abnormal. In addition to reporting anomalies to railway safety in real-time, artificial intelligence-based platforms also detect object types for a more comprehensive understanding of the current situation. Store event-based video clips, images and related data to achieve forensic analysis after the event.

In addition to improving security and response time, deployment scenario analysis at railway crossings can also improve operational efficiency by minimizing downtime and delays. Its machine learning ability reduces the time required for railway personnel to update the system manually. In this process, Nokia scenario analysis provides train operators with higher overall cost efficiency. It can also be integrated with many standard industrial cameras to reduce the total cost of ownership and improve the return on investment.

Michael Theiler, head of electrical system maintenance at BLT, said: “It is well known that it is difficult to ensure the safety of passengers, pedestrians, train operators and drivers at level crossings. The deployment with Nokia represents an encouraging step towards using analytics as another layer of protection in hazardous areas. Nokia scene Analysis acts as a set of intelligent “eyes” to prevent or mitigate the impact of events by providing critical information in real-time.

Roland Liem, head of railway safety products at Schweizer Electronics, said: “by combining level crossing systems and scenario analysis in a simple interface, this project with Nokia and BLT enables us to automate the interaction between level crossing systems and alarms to improve safety. This will enable railway operators to close barriers and deal with dangerous situations at intersections in real-time.”

Karsten Oberle, head of Nokia Railway, said: “as the first deployment of such a project in Europe, this project with Schweitzer Electronics and BLT enables us to address crossing security issues that are a priority for many railway operators. Now, we hope that the Nokia scenario analysis will be a key part of the future railway digital transformation. By integrating machine learning into the crossing system, we will be able to improve and improve the safety process in real-time. This will ensure that safety is always a top priority for train operators, workers and customers. ”


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