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Internet Of Things: What's Holding Us Back

The likes of Union Pacific, GE Power & Water, and ConocoPhillips are turning IoT hype into reality, but they want to do more. Here's what's still getting in the way.

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To see the problems in building the so-called Internet of Things, look at the trackside switches in what the railroad industry calls "dark territory." These switches are important -- if one is in the wrong position, a train could go off on a sidetrack spur at normal track speed and derail. But these areas are called dark territory because they're lightly used stretches of track in remote areas, where there are no automated signals, and probably no power lines and cellular links. Train operators must visually check that each switch is in the right position.

Union Pacific CIO Lynden Tennison would love to have a monitor that does nothing more than tell dispatchers and engineers which position a switch out in dark territory is in. For such a simple task, "it seems like it ought to be a $100 device, just to me and you living in the consumer tech world," Tennison says. But the sensor would need a power source and a communication link, and it would need to be hardened and weather-resistant. His goal: to get the cost to buy and implement each switch down below $10,000.

Tennison gets a lot of sales calls from analytics software vendors, each promising to help him sort out the data that the Internet of Things can generate for Union Pacific, the largest railroad company in the US. But Tennison's bigger problem is still having to do too much manual data collection. "I keep telling them that if you'll solve my sensor problem and get me a lot of cheap sensors out there that can collect a lot more information for me, I'll buy your analytics engine," he says.

That's the state of the game when it comes to the Internet of Things -- progress, but also frustrating barriers.

Companies in a variety of industries -- transportation, energy, heavy equipment, consumer goods, healthcare, hospitality, insurance -- are getting measurable results by analyzing data collected from all manner of machines, equipment, devices, appliances, and other networked "things."

Union Pacific says it reduced the number of train derailments caused by failed bearings by 75% by doing near-real-time analysis of data collected by sensors along its tracks, and now it's pouring millions of R&D dollars into new techniques, such as accelerometers on trains that feel for bumps that suggest a bad track. GE Power & Water says it helped Dubai Aluminum improve the fuel efficiency of its gas turbines by 1.5% while increasing output 3.4%, by analyzing sensor-collected operating data. Oil and gas company ConocoPhillips thinks it can save about $250 million a year in drilling costs by doing real-time measurement and analysis along the drill line to fine-tune factors such as speed and pressure on the drill bit. FedEx expects to save $9 million a year using sensors on its trucks that let it schedule dock assignments more efficiently.

Companies are moving more cautiously on the customer-facing Internet of Things, but they're making progress as well. John Deere can do remote, wireless diagnostics of some tractors and combines, for example. Guests at Disney World can wear MagicBands equipped with RFID chips that, when placed next to a reader, connect to their accounts and let them make purchases, access rides, and open their hotel rooms.

But companies are also hitting roadblocks. Union Pacific's Tennison says this whole area of "sensor-based, network-based diagnostic and predictive analytics" will be the biggest technology opportunity in his industry for the next 10 or 15 years. "Having said that, it's not moving as fast as I would like," he says.

Whirlpool CIO Michael Heim says "our toe is in the water on connected devices," as the company figures out the kind of connections customers really want in their homes, and what they'll pay for. Heim does see huge potential, and not just the cliché scenario of your refrigerator knowing all its contents and emailing you when the milk's running low. If customers let Whirlpool track appliance usage remotely, that would be a boon to product development, providing a window into what features people really use. What if the fridge told you when temperatures are varying, suggesting a pending failure, or your icemaker lost water pressure, suggesting a busted pipe might be spraying water all over your kitchen? What if your washer could be diagnosed remotely, since many appliances already generate electronic error codes? Even further out, what if people with elderly parents could monitor appliances remotely -- if Dad opened the fridge four times, used the stove, and ran some laundry, he's probably OK.

While Whirlpool product teams are working on all the foundations for this kind of connectivity, Heim says, "those are more futuristic than you think."

Here are the main IoT challenges companies are wrestling with.

The data isn't good enough.
One of the myths about the Internet of Things is that companies have all the data they need, but their real challenge is making sense of it. In reality, the cost of collecting some kinds of data remains too high, the quality of the data isn't always good enough, and it remains difficult to integrate multiple data sources.

Let's start with getting enough data. The cost of a sensor includes not just the device, but also the installation, maintenance, connectivity, and power. And even in tightly controlled environments such as a factory, a lot of legacy equipment wasn't built for Internet connectivity, making security and integration problematic.

"We've come a long way, and we're leveraging the heck out of what we do have out there," Tennison says. "I'm just saying to myself, 'If I had 10 times or 20 times as many collection points as I do today, how much better could we get?' That seems to me right now the biggest problem."

Data quality is a problem that GE Power & Water CIO Jim Fowler is putting in front of his $28 billion-a-year unit's CEO and other company leaders. The monitoring and alerting systems GE is developing for maintenance of its gas and wind turbines, for example, draw on many types of data, including customers' operational data and their inventories of replacement parts.

The data collected today is good enough to improve operations -- GE says wind-power company First Wind, for example, improved energy output 3% from existing turbines by monitoring weather and operating conditions and changing the blade pitch on its turbines for better efficiency. But the data

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Chris Murphy is editor of InformationWeek and co-chair of the InformationWeek Conference. He has been covering technology leadership and CIO strategy issues for InformationWeek since 1999. Before that, he was editor of the Budapest Business Journal, a business newspaper in ... View Full Bio

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User Rank: Moderator
5/5/2014 | 4:34:00 PM
Re: IoT software vs. hardware
The railway and oil industry requirements are the same for the most part (like any other industry, resource-based or other that are remote from urbanania).

Remote locations, little WiFi, power in short supply, and the environmental challanges. Solar powered units would resolve some of this potentially but you also need some fail safes built in to any IoT application. Like when the power to traffic lights goes off at an intersection, you can get a Bobby to manually direct traffic. Any implementation requires an audit trail of real-time testing that it is working and a backup (tested to fall over to when it isn't).
Drew Conry-Murray
Drew Conry-Murray,
User Rank: Ninja
5/5/2014 | 3:51:42 PM
Re: IoT software vs. hardware
I'm surprised about the lack of concern about analytical capabilities too. The security industry has been wrestling for years about how to identify actionable information from massive quantities of data. Maybe with IoT you're dealing with a small subset of known data types (pressure, temperature, vibration, etc), which makes it less about needles and haystacks.
User Rank: Author
5/5/2014 | 2:17:46 PM
Re: IoT with more capable platforms
Manu, thanks for the perspective. It does seem like there's a role for a management platform in here somewhere that is still evolving today. 
User Rank: Apprentice
5/5/2014 | 1:49:29 PM
IoT with more capable platforms
Chris - interesting article. I think the way we will be able to address some of this complexity and integration challenges is with the platform (or middleware) taking up a larger burden. If we continue to custom build each solution (as the article describes we do today) with massive integration efforts, security, burdened devices and heavy apps that have to embed connectivity, networking, data massaging, QoS etc, it will be a long time before we get to 50 billion useful connected devices! 

I believe some of the burden will be delegated to platforms that can then enable more focused devices and "thin" apps - while providing the networking, security, contextual intelligencem modularity, data flow/access and APIs to build solutions faster. 

User Rank: Author
5/5/2014 | 11:34:27 AM
Re: IoT software vs. hardware
The lack of deep concern about analytical capabilities was one of the biggest surprises to me from the reporting in this article. If others have had a different experience, glad to hear about it.

In terms of sensors, we'll see about how much industry-specific adaptation is needed. Bill Ruh of GE noted that in the mechanical world, measuring vibration is something of a universal need -- it's rarely a good thing with machines. However, not all the innovation in sensors will be hardware driven -- virtual sensors, or software-based sensors that combine inputs from multiple sensors, will emerge as companies needs get more sophisticated.   

User Rank: Author
5/5/2014 | 10:57:28 AM
IoT software vs. hardware
Tennison's story about asking analytics software vendors to solve his sensor hardware problem is striking. It makes me wonder if we are much further along on the software side than the hardware side regarding IoT.

Also his problem is specialized to the railroad industry -- and there will be examples that need to be customized for every vertical. How will sensor manufacturers achieve affordable scale? Lots of interesting food for thought here.
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