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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: Author
5/9/2014 | 4:08:07 PM
Who Gets the Data?
An interesting idea that I didn't explore, that I heard in a follow-up chat this week with the folks at M2Mi (thanks Manu), was about who gets access to the Internet of things data. Jim Fowler, quoted in the article, talked about this at the IW Conference -- aobut how GE only gets access to power plant data if the customer continues to see the value in sharing it. But the M2Mi folks brought up other parties who will want access -- for example, the lender who owns a piece of equipment you're leasing, to make sure you're doing the maintenance so it'll have the expected residual value at lease end. A lot to think abot there in terms of who gets access to the data beyond the simple Maker-Owner.  
User Rank: Apprentice
5/7/2014 | 4:28:16 PM
Re: IoT software vs. hardware
At Packet Dynamics we realized that the 'dark territory' or areas not covered by cellular M2M services exist not only in the U.S but also globally. Infrastructure players whether rail, pipeline, electrical transmission, etc. all need to communicate to end nodes that might never be covered by GSM/LTE. The Cloud can't just exist in the colored areas on AT&T, Verizon, and Sprint's coverage maps. 

We provide beyond-line-of-sight communications for M2M and cloud applications using High Frequency radio links.  We went back to HF, an old school spectrum that still works, and added the latest in radio technology (waveforms, error correction, etc) to solve real world industrial problems. It's not the glamorous side of the Cloud, but for companies with equipment scattered across the fly-over states or in third world countries it does solve a major problem.

Dan Conner
User Rank: Ninja
5/7/2014 | 7:32:40 AM
Re: IoT software vs. hardware
The really large IoT solutions will need the cloud to be truly effective but right now those solutions are few and far between.  I can't think of many companies that cover the area that Union Pacific covers with the need to monitor many points along the way.  Even companies like UPS or Fedex don't need to see the condition of every mile of road that they travel.  I think some government projects could become this big but if you're looking to track trucks for a medium sized company via GPS then moving to the cloud isn't going to be as critical for success.  
User Rank: Author
5/6/2014 | 2:53:51 PM
Re: IoT software vs. hardware
Insightful article, Chris. Unless you've been out to the remote areas where these pipelines and railines have been built, it's easy to underestimate just how far-flung and distant this infrastructure is -- and what it will take to develop sensors that would stay powered and in touch. But I sense the integration of data question may be equally challenging, and another reason why the IoT will work in some fields, and take much longer in others.
User Rank: Ninja
5/6/2014 | 2:17:20 AM
Re: IoT software vs. hardware
Without electricity, communications and the internet could not exist, without the internet, Cloud computing would not exist, I think that the majority of the IoT will need the Cloud. Hence, without the Cloud a lot of IoT's potential might not materialize. The inter-linked and dependent environment of technology might provide a break-through, but I feel that this break-through might just be written off as the normal pace of technological progress.
User Rank: Apprentice
5/5/2014 | 7:21:35 PM
FedEx for Data
Good perspectives.  IoT, especially in the industrial world is not as simple as a NEST appliance.  There are several considerations here:  the device, the data, the analytics, and then the data tranport mechanism.  On top of that, there are almost 2 billion legacy devices already spitting out data but until now there hasn't been an easy way to secure and backhaul that data.

The data transportation question, is equivalent to FedEx for packages.  An organization just wants to securely transport data from point A to point B.  You don't really care how the package (or data) gets there, just that it does on time.  And, most of todays sensors are also still serial devices - not IP-based.  

This is where virtual networks through software-defined architectures meets the Internet of things.  Virtualization makes the problem a whole lot easier to solve.  


Jay Friedman

Distrix (
User Rank: Apprentice
5/5/2014 | 5:20:41 PM
Delivering the data
Interesting that the focus is mostly on the edge (e.g. sensors) and the centre (e.g. cloud-based analytics) without much discussion of the data-sharing infrastructure needed to support any end-to-end system.

Whether the system designer leans-toward sensor-based (edge) computation or, alternatively, 'thin' apps connected via a cloud service, it is inevitable that both will be required in any business-critical system, and furthermore, device-to-device data-sharing (e.g. for local real-time control) will often be required too (e.g. when the latencies to/from the cloud are too long). So a lot more attention needs to be given to the real-time data-sharing platforms that will be needed to underpin and enable these IoT systems. Many system designers will recognize this as the 'elephant in the room' since commentators tend to focus on: 1/ smart sensors and 2/ big-data analytics, while assuming some kind of wireless connectively alone is sufficient for real-time data-sharing. Fortunately the technology exists (e.g. the OMG's DDS specification) and is standardized and proven. Hopefully we'll start to see a lot more discussion of the system infrastructure...rather than just the data sources and sinks that it connects. Ubiquitous, real-time, secure data availability won't just happen.              
User Rank: Author
5/5/2014 | 5:03:32 PM
Re: IoT software vs. hardware
We need a bandwidth breakthrough, also. Bonus points for connecting Iron Man to this debate.
User Rank: Author
5/5/2014 | 4:57:11 PM
Re: IoT software vs. hardware
The power limitation is definitely true, Tom. One difference from smartphones is that industrial uses often involve relatively low power demands -- sending small bits of data back, but needing to stay powered over many months because replacing/recharging is difficult.  
Thomas Claburn
Thomas Claburn,
User Rank: Author
5/5/2014 | 4:51:32 PM
Re: IoT software vs. hardware
I find it interesting that the IoT is hobbled by the same thing that limits smartphones: power. We need a breakthrough in power storage and generation that improves current technology by an order of magnitude, something along the lines of Iron Man's arc reactor.
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