Imperfect Data

The U.S. railroads are proud of their rising efficiency. U.S. rail freight rates are half of what they were in 1981 in inflation-adjusted dollars, the Association of American Railroads is fond of noting. Railroads move a ton of freight 484 miles on a gallon of fuel, up from 235 miles in 1980. Technology plays a role there as well: UP has been testing a system on its Wyoming-to-Chicago coal trains that tells a driver when to throttle up or down to maximize fuel savings.

And yet this complicated network runs on imperfect data. As companies consider the future of analytics, one of the big limitations still is getting the needed data at an affordable price.

For railroads, location data is a big gap. While UP has GPS tracking on several thousand locomotives, GPS isn't reliable enough for safe dispatching and switching of trains--it isn't accurate enough to tell which of two parallel tracks a train is on. So the tracks have a location sensor about every 15 miles that tells a central dispatcher where a train is, leaving a lot of blind spots. And even at those markers, the system knows only that a train passed the spot. In terms of where a train will be in the next five minutes, one traveling 60 mph and accelerating is a lot different from one going 40 mph and slowing down.

Another reason trains don't use GPS is because there isn't universal cellular coverage along the tracks, especially in the vast expanses of the Western U.S., for trains to continually transmit their precise locations. Until the trains get that precise location data and ubiquitous wireless data coverage, railroads can't do a lot of the sophisticated routing, monitoring, and automated controls envisioned for the Internet of things.

"If I could wave my magic wand, I would love to have 4G networks everywhere across my tracks," Tennison says. "That would really change the game for us." The industry is funding research on space-based navigation options like GPS, hoping to find something that meets its requirements.

Sensors are another linchpin to the Internet of things. They're how we'll extract the data from all of these devices. Tennison can quickly spin out a list of places on a railcar he'd like to put sensors: on bearings to measure vibration to anticipate a failure; on a tanker valve to measure pressure and know if there's a leak of toxic gas; on doors to know if a high-value container has been opened. But it would cost UP $500 to $600 to put eight to 10 battery-powered sensors on a railcar. The cost needs to get closer to $200 to be practical. "I think that's coming, but it's coming slower than I wish it was coming," Tennison says.

Those sensors would need to last on a railcar for five to seven years without replacement. That rules out today's battery-powered sensors and likely will require "energy harvesting"--techniques such as capturing the energy from a train braking to use as power.

And UP would need to persuade the industry to standardize on sensors, network standards, and messaging.

Another challenge has to do with how quickly companies can do analytics on the reams of data they're collecting. To understanding that challenge, it's worth a quick detour from railroads to power plants.