Community Insights Transportation

Railways on Track for Digital Transformation

shutterstock_614809565

Image: Shutterstock.com

(“Community Insights” are articles by members of the Techonomy community, contributing to the ongoing dialogue that is our raison d’être.)

Transportation began with the invention of the wheel, back around 3500 B.C.

And today, innovation still often centers on transport.  Improving our roads, bridges, rail and overall infrastructure is back in the headlines because we badly need to invest, rehabilitate, and improve systems, especially in the U.S. It’s time to get moving and use innovation and leverage technology to create smarter, safer and more efficient transportation networks.

Big data, analytics and the internet of things (IoT) are poised to have widespread impact across all modes of transportation and rail is no exception. The rail industry is one of the oldest and most conservative, but like every other business, efficiency, cost savings and safety are always top of mind.

Freight railroads play a key role in the U.S. economy for moving coal, oil and myriad other payloads in containers across the country. The U.S. is known for having one of the best freight railroad networks in the world, but there is plenty of opportunity for improvement.

It starts with the quality of the data. Just think for a moment about all the data a freight train generates: locomotive parts, tonnage, speed, fuel, wayside communications, throttle position, and even the number of times the wheels rotate. The data collected can be endless if you begin to measure all the parts, movements, cargo and assets. Some say that freight railroads are generating “brontobytes” of data (that’s a million times more than a petabyte). But data collection is only a burden if you can’t capitalize on the information. Which leads me to analytics.

Advanced machine learning and video analytics are providing the foundation for truly transformative solutions to old problems. Maintenance is a great example. The traditional scheduled maintenance approach means costly downtime and heavy use of resources for sometimes unnecessary procedures. Using sensor data and machine learning, rail operators can take a more prudent approach by learning about the early warning signals for preemptive intervention. Determining maintenance procedures with the help of analytics allows railway operators to more accurately determine the remaining usefulness and safe life of parts.

Similarly, analytics can help optimize scheduling and coordination of resources. Even small refinements can result in huge cost savings and revenue generation for the railroads.

Video is also starting to play a key role for freight railroads– especially where instrumentation with sensors is not practical. In many ways, video is becoming the new killer sensor– after all, they do say a picture is worth a thousand words. Video can be used for real-time visual inspection of the rail lines. On locomotives and containers video can see a variety of elements including mechanical problems, intruders, and smugglers, as well as safety issues along the track. There are many other use cases.

And there are plenty of similar uses in passenger rail. Safety is clearly key but innovative rail operators are now also leveraging analytics to better understand passenger flow to improve customer service. This enables them to differentiate themselves in an increasingly competitive market, versus other often less enjoyable forms of transportation.

Its full steam ahead on all fronts for analytics and IoT in rail. Exciting innovations are to come as this sector continue to gain momentum.

Tags: , , , , ,