Bihrle Applied Research has announced that, in conjunction with BNSF Railway (BNSF), it has successfully demonstrated the processing of tens of thousands of images at a time covering hundreds of miles of track for the automatic detection, classification and reporting of rail conditions. This was possible using RailVision – a computer vision technology solution developed by Bihrle and BNSF in support of BNSF’s UAS (unmanned aerial system) research initiatives.
RailVision enables BNSF to automatically process images collected by drones during supplemental railway inspection flights and generates actionable reports in a fraction of the time required by traditional methods. The success of RailVision has enabled BNSF to apply its use to expanded operations.
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“Bihrle’s computer vision capabilities have been used in conjunction with our railway safety enhancement research and the FAA’s Pathfinder Program,” said Todd Graetz, Director, Technology Services at BNSF. “The breadth of railway anomaly detection capabilities provided by Bihrle allows us to further research into the use of long range UAS.”
“Commercial UAS offers a unique visual perspective for monitoring and inspection of critical infrastructure like railroads, power lines and pipelines,” said Jack Ralston, President of Bihrle Applied Research. “UAS are typically flown with one or more imaging capabilities that result in terabytes of images and their associated metadata. Bihrle has been working with BNSF for over 4 years to create an automated computer vision solution that processes the images, allowing human Subject Matter Experts to review the actual findings rather than being burdened with the task of looking at raw image files, thereby fully exploiting the value of UAS based inspection.”