Swiss transit authority uses AI monitoring to secure rails

Baselland Transport AG (BLT), a Swiss public transportation firm providing bus and rail services in Münchenstein, Switzerland, has incorporated a threat detection system to ensure the safety of railroad crossings. The AI-based system, Scene Analytics from Nokia and Schweizer Electronics, applies computer vision and machine learning technologies for real-time monitoring and analysis.

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.

To mitigate these safety risks, 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, the AI-based platform detects the object type and stores event-based video clips, images and associated data.

Besides improving safety and response time, the platform can also increase operational efficiencies by minimizing downtime and delays. Its machine learning capability reduces the time investment required by rail personnel to manually update the system. It can also be integrated with many standard industry cameras.

ON DEMAND: Business-impacting events such as severe weather, man-made disasters, and supply chain disruption are increasing in frequency and making impacts around the globe.

In today's rapidly evolving security landscape, organizations face an ever-growing array of disruptive events, security threats and risks. Traditional reactive approaches to security intelligence often leave businesses vulnerable and ill-prepared to anticipate and mitigate emerging threats that could impact the safety of their people, facilities or operations.