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Nokia and Schweizer Electronics deploy AI-based video analytics to improve railroad safety
Nokia has announced the deployment of its Scene Analytics solution for Baselland Transport AG ( BLT ) in Münchenstein , Switzerland . The AIbased system applies computer vision and Machine Learning technologies for realtime 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 .” p
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