Can Internet of Things help solve the Malaysia 370 mystery?

Posted on 13th March 2014 in Internet of Things, M2M, transportation

It appears from a Wall St. Journal article  that Malaysia Air 370’s Rolls-Royce Trent 800 engines may have had built-in sensors

Rolls-Royce Trent 800 jet engine

that allowed the engines to send real-time operating data to Rolls-Royce for analysis. According to the WSJ, the data may indicate that the plane flew for an additional four hours after its last radio transmissions.

Whether or not this proves to be true, it does give a preview of what life will be like when the IoT is fully functional: real-time data will become a critical tool in transportation management and safety. In this case the data might help locate the wreckage. In others, the fact that it will allow traffic controllers, whether on the ground or in the air, to react to danger in real time, will save lives. 

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Seeing’s believing: the mother of all #IoT infographics is here!

Posted on 5th March 2014 in agriculture, design, Internet of Things, M2M, manufacturing, marketing

Like wow!  Trevor Harwood at the go-to IoT site Postscapes has teamed up with Harbor Research to create a “little” infographic (by my calculations it is about 2 miles horizontally by 3 miles vertically!!) that tells all you need to know about the IoT (download here: I wouldn’t attempt to do a screen grab: couldn’t do justice to it!).

I’ve been looking at it for several hours, and still haven’t processed all the information, but I think you’ll find it invaluable to introduce newbies to the IoT and all of its aspects (I was particularly impressed by several of the case studies that I hadn’t read about before).

Download it now, then study it carefully. Nice job!

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Libelium’s Alicia Asín Pérez: crafting an IoT leader from the ground up!

Posted on 3rd March 2014 in agriculture, collaboration, environmental, government, health, Internet of Things, M2M, manufacturing, mobile, open data

Any time you run into a leading IoT engineer who says she draws inspiration from the early NYC skyscrapers (Why? “..Most of them were built during the Great Depression and make me think that in big crisis like the one we are living there are also the greatest opportunities for creating amazing things.”) you know you’re in for some outside-the-box thinking!

Alicia Asín Pérez of Libelium

That’s the case with Libelium’s Alicia Asín Pérez, who I had a chance to interview just before she was to leave for this year’s Mobile World Congress, where Libelium unveiled its new Smart Water sensors, the latest addition to the eight-year old company’s impressive list of IoT sensors.

What impresses me the most about the company is how Asín and co-founder/CTO David Gascón have pursued their vision of an open-source system (their Waspmote platform “sends any sensors’ data using any communication protocol to any information system so that anyone can play in the IoT”) without compromise from when they started the company.

After attending the Universidad de Zaragoza, the young engineers decided to enter the decidedly un-cool field of hardware, not app design.

They didn’t want to get trapped into serving only one industry vertical (at present they’re serving smart cities, smart water, smart metering, smart environment, security and emergencies, logistics, industrial control, smart agriculture, smart animal farming, home automation, and ehealth.  Any areas they’re not serving?), so they refused to deal with VCs, bootstrapping the company before the days of crowdsourcing. They even appeared on a quiz show for entrepreneurs to get cash, and were prepared to head to Hollywood quiz shows (Asín knows a lot about a lot of subjects, LOL!) if need be.

Libelium is intent about focusing on open source solutions, walking their talk to the point of even using Linux computers.

They also get it about one of my “Essential Truths” of the IoT, that it “democratizes innovation.”  On one hand, Libelium has partnered with major firms such as IBM (with the “Internet Starter Kit”), and, on the other, 30% of its revenues come from its work with the “Maker Movement,” through its “Cooking Hacks” division, which includes:

  • +4000 products for DIY projects
  • Waspmote starter kits
  • Step-by step-tutorials to get started
  • A community forum

Asin sounds like a revolutionary with her call for “democratizing the technology of the Internet of Things,” and speaks proudly of how Libelium quickly created a Radiation Sensor Board used by an ad-hoc network of activists who documented radiation levels after the Fukushima accident. Speaking to Postscapes, she emphasized that while IoT projects by major companies are important, it’s equally important to use the IoT to empower individuals:

“When you are in front of such a revolution, you can neglect individuals. It is a big mistake thinking about the IoT players as big companies or just companies. If we look at the general sociopolitical situation, at the citizen movements all across the globe, we see that individuals are just claiming more transparency and not depending on governments and big companies for accessing data: people want Open Data, Open Source, Open Hardware, Open Funding… Because of that, we see projects like Safecast for detecting radiation levels in Fukushima or Air Quality Egg in the Netherlands. People want to do things on their own and are finding support in all the crowdfunding platforms like Kickstarter and companies backing open hardware that allows them to access inexpensive technology. For example, we just launched a kit to experiment with eHealth and we have already sold more than 1,000 units. People are being more creative and innovative than ever, and everyone needs tools for doing that. Those ‘tools’ are sensors and providing them is our vision.” (my emphasis).

It’s too early in the IoT’s evolution to predict the ultimate winners, but I suspect that Libelium’s passion for open systems, its technical expertise at creating a growing array of sensors, and its ability to partner with both big and small firms will help it prosper over the long haul.

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Follow-up: Winners in Postscapes’ annual best-of-the-IoT contest

Posted on 5th February 2014 in automotive, energy, environmental, government, health, home automation, Internet of Things, manufacturing, mobile, transportation

Following up on my recent post on my favorite nominees for the 2013 Postscapes best-of-the-IoT contest, here are the actual winners.  What do you think??

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Crucially important cautionary note about data’s limits!

Posted on 4th February 2014 in Internet of Things, open data, US government

I yield to no one in my passion for liberating data, and for its potential role in improving decision-making. It’s essential to full realization of the Internet of Things, and yes, it can even save lives (not to mention baseball teams, witness Michael Lewis’ wonderful Moneyball!). However, I implore you to read “Why Quants Don’t Know Everything,” a gem by Felix Salmon that’s tucked into the current Wired issue. It documents a disturbing pattern of how decision-making in everything from baseball to, yes, the NSA, can be distorted — with serious consequences, when the “quants” take over completely and data is followed blindly. Salmon begins with the NSA’s insatiable appetite for data:

“Once it was clear that the NSA could do something, it seemed inarguable that the agency should do it—even after the bounds of information overload (billions of records added to bulging databases every day) or basic decency (spying on allied heads of state, for example) had long since been surpassed. The value of every marginal gigabyte of high tech signals intelligence was, at least in theory, quantifiable. The downside—the inability to prioritize essential intelligence and act on it; the damage to America’s democratic legitimacy—was not. As a result, during the past couple of decades spycraft went from being a pursuit driven by human judgment calls to one driven by technical capability.”

Let me emphasize: technical capability came to trump human judgment calls. I suspect there’s probably not too much question among you, dear readers, that the NSA went to far. But Salmon sees a broader problem with unchecked faith in data:

“The reason the quants win is that they’re almost always right—at least at first. They find numerical patterns or invent ingenious algorithms that increase profits or solve problems in ways that no amount of subjective experience can match. But what happens after the quants win is not always the data-driven paradise that they and their boosters expected. The more a field is run by a system, the more that system creates incentives for everyone (employees, customers, competitors) to change their behavior in perverse ways—providing more of whatever the system is designed to measure and produce, whether that actually creates any value or not. It’s a problem that can’t be solved until the quants learn a little bit from the old-fashioned ways of thinking they’ve displaced.” (my emphasis)

Salmon goes on to show parallel stages in a wide range of fields where data is in the ascendancy:

  1.  “pre-disruption.” The Neanderthal period, before data is applied to big problems.
  2. “disruption.” Example they use is 2012 Obama campaign, where the technologists held sway, targeted voters down to the individual level based on data. You know what happened.
  3. “overshoot.” Here’s where things go off the track:”The most common problem is that all these new systems—metrics, algo­rithms, automated decisionmaking processes—result in humans gaming the system in rational but often unpredictable ways. (my emphasis) Sociologist Donald T. Campbell noted this dynamic back in the ’70s, when he articulated what’s come to be known as Campbell’s law: “The more any quantitative social indicator is used for social decision-making,” he wrote, “the more subject it will be to corruption pressures and the more apt it will be to distort and corrupt the social processes it is intended to monitor.”On a managerial level, once the quants come into an industry and disrupt it, they often don’t know when to stop. They tend not to have decades of institutional knowledge about the field in which they have found themselves. And once they’re empowered, quants tend to create systems that favor something pretty close to cheating. (again, my emphasis) As soon as managers pick a numerical metric as a way to measure whether they’re achieving their desired outcome, everybody starts maximizing that metric rather than doing the rest of their job—just as Campbell’s law predicts.”

    He then gives a number of illustrations including “teaching to tests” and, most infamously, the bank meltdown  (I was particularly struck by the one dealing with serious problems in policing: um, it can kill…) that can come as a result of pre-occupation with data. Have you seen this in your field??

  4. “synthesis.”  My father used to say that there was an inverse relationship between the amount of education you had and your amount of common sense (he was a little too intimidating for me to point out that he had a Ph.D….).  Here’s where the smart guys and gals learn to put data in perspective:”It’s increasingly clear that for smart organizations, living by numbers alone simply won’t work. That’s why they arrive at stage four: synthesis—the practice of marrying quantitative insights with old-fashioned subjective experience. Nate Silver himself has written thoughtfully about examples of this in his book, The Signal and the Noise. He cites baseball, which in the post-Moneyball era adopted a ‘fusion approach’ that leans on both statistics and scouting. Silver credits it with delivering the Boston Red Sox’s first World Series title in 86 years. (LOL: my emphasis!) Or consider weather forecasting: The National Weather Service employs meteorologists who, understanding the dynamics of weather systems, can improve forecasts by as much as 25 percent compared with computers alone. A similar synthesis holds in eco­nomic forecasting: Adding human judgment to statistical methods makes results roughly 15 percent more accurate. And it’s even true in chess: While the best computers can now easily beat the best humans, they can in turn be beaten by humans aided by computers.”

I’ve been concerned for a while that the downside of vast quantities of real-time data is that decision-makers may ignore time-honored perspective, horse sense, whatever you call it, and may just get whip-sawed by constantly changing data.

So yes, there will be a need for living, breathing managers in the era of the Internet of Things, even ones with grey hair! It will take time, and probably a lot of trial-and-error, but smart companies will attain that synthesis of qualitative insights and “old-fashioned subjective experience.

I beg you: please read this entire article, save it, and share it: it’s a bit of critical insight that may just get drowned out by people like me calling for more, and more rapid, sharing of data. 

Whew. My conscience feels redeemed!

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Google makes IoT mainstream

Posted on 21st January 2014 in design, home automation, Internet of Things, M2M, management, strategy

We won’t know for a while the direct impact that Google’s stunning, multi-billion dollar acquisition of Nest will have, but one thing is for sure: it’s given the IoT an unprecedented level of recognition, and my bet is that history will judge that as a critical step in the IoT’s commercialization. After all, Nest only has two products, and their price premium compared to competing thermostats and smoke detectors meant they were definitely niche players.  Now, the “Google Effect” will mean that they’ll get a disproportionate amount of media attention, just as the driverless car has.

That’s no small thing, especially for the IoT in general, which got more attention in 2013, but, IMHO, still remains unheard of among the general public.  I suspect that the phrase “Internet of Things” got more exposure last week because of the Nest deal than it ever had in the past.

Nest 2.0 thermostat

Nest 2.0 thermostat

Of course, there are some big imponderables in the deal. Google’s past in consumer acquisitions (i.e., Motorola) isn’t exactly stunningly successful, and it’s hard to tell now how much they’ll want to grow the Nest line, or whether they’ll decide to make radical cuts in the devices’ prices to gain market share. I do suspect that one part of Nest’s strategy, adoption of the Apple closed-standards approach, will go bye-bye: not only is it incompatible with the whole Android philosophy, but it also makes no sense from an IoT standpoint, since the only way the IoT will ever succeed will be by standardizing on a small number of open systems (I’m a FIERCE Mac zealot, but still think that history will judge their devotion to a closed system to be a quirk: I always look to nature for inspiration, and nature doesn’t do things that way!).

The other big question about the deal is whether there will be a Chinese wall between data from Nest devices and Google’s omniverous data maw.  Nest CEO Tony Fadell says that the data will remain with Nest, but that seems highly-unlikely over time. We shall see…

At any rate, it seems to me that this is, on whole, a critical watershed in the IoT’s commercialization, and we’re likely to see new interest among the general business community and the public as a result!

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Fie on the Polar Vortex! Are there #IoT sensors to avoid burst pipes?

Posted on 9th January 2014 in environmental, Internet of Things, maintenance

The weather so far in 2014 in the US has been insane, with the “Polar Vortex” putting much of the nation in the deep freeze. One costly result? A plague of burst pipes, including my wife’s hospital, and my son’s university.

I did a quick search and couldn’t find an IoT sensor to detect bulging pipes in time to shut them off, but I’m sure someone has developed one as part of a “smart building” strategy. Let me know if you make one, and I’ll spread the word. 

Aside to Sen. Imhofe: I know you’re chortling about this, but NPR reported recently that as a result of global warming winters in general will be moderating but there will be more extreme weather events such as this one. Checked the pipes in your basement, sir?

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CK Kerley brings pizzazz to IoT marketing!

Posted on 7th January 2014 in Internet of Things, M2M, marketing

I’ve been away, really celebrating the holidays with my family and working on revisions to my e-book on managing the IoT for mainstream companies.  What better way to return than with a new publication that really gives some oomph to marketing the IoT?

The Smart Revolution

I met CK Kerley when she made some nice comments about my SmartStuff e-book intro to the IoT, and have been impressed by the energy and pizzazz that she brings to the marketing aspect of the IoT — elegant tech can only take you so far, and then you need to sell the stuff!

Now CK has a free e-book on marketing the IoT, The Smart Revolution, and it’s a great jumping off point for planning your own IoT marketing strategy. You can quickly finish it one one sitting — then come back to it again and again for future inspiration.

What comes through time and time again throughout the brief tome is something I hope also comes through in this blog and in my forthcoming e-book: the IoT won’t just make current things (literally and figuratively) better: if we fully exploit its potential, it will result in fundamental transformation!

Kerley emphasizes that marketers don’t have any choice about whether to embrace smart devices: consumers will force them to do so:

“The benefits of smart capabilities will have profound implications upon tomorrow’s customers who will be much more demanding, much more impatient, and much more savvy, with much higher standards.

“Mark my words, marketers: Dumb things won’t merely be an inconvenience to your customers; they will be all but intolerable to them—and wholly irrelevant in the 21st century marketplace. While smart brands give marketers a competitive advantage today, that advantage will rapidly transform into tomorrow’s cost of entry.”

Kerley also emphasizes that this transformation will be more than bells-and-whistles for consumers: it will have a profound, positive impact on their quality of life:

“Now marketers can move from developing individual dumb products for customers to engineering fuller, smart solutions that truly change customers’ lives. You are enabled to remove the mystery that has shrouded entire areas of your audiences’ lives and infuse it with transparency—empowering them to make better decisions that lead to better outcomes.

“Marketers can eliminate the overwhelming complexity that has plagued their customers’ lives and, through their smart brands, replace it with sheer simplicity. And you can expand the roles your brands play in customers’ activities—a move that your markets will welcome because it will transform static components into dynamic experiences for them.

“Finally, in a sea change for companies, we can migrate from mass- producing products shipped from our factories to micro-personalizing offerings that are only truly complete when they are in the hands of our customers.”

She’s taken the tack of organizing IoT marketing in terms of 5 basic principles, with several brand examples for each to show that the IoT is a current reality, not a laboratory dream. Think of those examples as ammunition to convince skeptical executives that the IoT is a reality and the time to develop a strategy is now!

Here they are:

  1. Value: “smart brands expand value by transforming single, dumb products into fuller, smart solutions.”  Examples:
    1. Asthmapolis Smart Inhaler: “transforming a product that manages asthma attacks into a solution that works to prevent asthmatic episodes” (because it’s location aware) (see my post about the TellSpec food analyzer)
    2. Nike+ Smart Basketball Shoes: “Transforming a sporting accessory into a fitness partner that tracks players’ progress in real time”
  2. Empowerment: “smart brands empower customers through new insights that drive better outcomes,” such as self-monitoring Quantified Self devices’ that empower patients to be full partners in their health care. Examples:
    1. MC10’s Smart BioStamp: “24/7 Monitoring of vital statistics takes the mystery out of health and arms patients and physicians with the data to provide better care.”
    2. Jawbone UP: My fav Xmas present? Other than the totally-outside-the-box, totally-unexpected MacBook Pro, I love my new Jawbone UP, and the ability it gives me to track my fitness activities!
  3. Simplicity: “smart brands remove complexity — and replace it with simplicity.”
    1. GlowCaps Smart Pill Bottles: “Removing the complexity of remembering to take medication by turning the simple pill bottle into a smart reminder.” Still one of my fav IoT pioneers!
    2. IntelligentM SmartBand: “replacing the complexity of hand-hygiene compliance by turning healthcare workers’ wristbands into personal, real-time reminders.” This is my fav of Kerley’s examples: one of of my cousins got very, very sick at America’s finest hospital (it may or may not be in Baltimore…) from a Hospital-Acquired Infection — which usually occur because personnel forget to wash their hands! “Through RFID technology, the SmartBand works by communicating with other objects (such as IV bags) that reminds workers to sanitize their hands by buzzing three times. Then, once workers have thoroughly washed all areas of their hands for the correct amount of time, the wristband buzzes once, signaling workers that they can proceed with their treatments.”  How cool is that???
    3. Tagg Smart Pet Tracker: “Eliminating the complexity of keeping dogs in the yard by simply turning their collar into a smart pet tracker.”
  4. Experience: “Smart brands turn static elements into dynamic experiences.” Examples:

    1. Vail Resorts Smart Ski Pass: “turning the dumb ski pass into a dynamic device unleashes an entirely new skiing experience.” I got a little preview of this transformation skiing in the Berkshires last year: the lift ticket was a glorified RFID tag. However, this goes far beyond!”When visitors get to each lift, their tickets—enabled with RFID technology—are scanned and automatically record each skier’s lift rides, calculate their vertical skiing feet and tally their ski days.”To review progress, users simply need to access the online site or mobile app replete with stats, maps and achievements that tell the story of the customers’ “epic” days or “epic” seasons—with Vail featuring a separate kids’ site for children under 13. The site, app and smart ski ticket do more than just record data, they award skiers with special pins commemorating hundreds of milestones, special adventures and unique accomplishments for each day—and each season—at each of Vail’s collection of ski resorts.” Neat!
    2. GolfSense Smart Golf Sensor: “a smart globe becomes a new virtual participant — and a golfer’s secret weapon — in the game experience.” OK, this one hurts: for a short while this Fall, before I did a competitive products search, I thought I had the KILLER IoT golfing app. Alas, while it did have some unique elements, this and some other apps do a good enough job that there was no reason to develop mine. Fame and fortune remain around the bend (or on the next tee).
  5. Personalization: “smart brands are micro-personalized by customers, not mass-produced by companies.” Examples:
    1. The Nest themostat: everyone’s IoT poster child. Its sensors even observe if the house is vacant (although I’ve always worried that you might just be absorbed in a book for hours on end, not moving, so the Nest would decide to put you on chill. What’s your actual experience with it??)
    2. Target’s Smart Shopping Experience: (in the design phase) “An idea that turns a big-box store full of products into a personalized store tailored to your specific needs.” I will ignore the opportunity of a bad joke at Target’s expense…

So check it out, and, if you’re a corporate marketer, add your voice to our chorus to get your C-level execs fired up about the IoT’s revolutionary potential. Thanks, CK!

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TellSpec: IoT device that can be a life-saver — and the killer app!

Posted on 10th December 2013 in design, environmental, health, Internet of Things, M2M

Whenever someone tries to dismiss the Internet of Things as a nice future vision, I love to rebut them with an example — such as the bassinettes in the Toronto Hospital for  Sick Children that allow doctors to diagnose a life-threatening infection a day before there are visible symptoms — that shows the IoT’s not only a reality, but is also saving lives!   That usually stops them in their tracks.   .

Now there’s a great new example on the horizon: the TellSpec food inspector.

In fact, because of the service’s three components, I’d say it’s a near-perfect example if you want to introduce the IoT to someone! Once in widespread use, it might well be the “killer app” that finally makes the IoT a household phrase — extremely useful (and easy to use), affordable, and allowing you to do something that couldn’t be done before.

For a variety of reasons, the rate of food allergies is increasing alarmingly, and adults with gluten allergies or parents whose kids are allergic to peanuts can’t always depend on package labels or appearances to warn them of when a given food may trigger a deadly attack of anaphylaxis. Then there’s the rest of us, who are increasingly dubious about whether our foods include pesticides, transfats or other unwanted substances. Or, we may just want to track our calorie consumption. TaDa! The TellSpec!

The crowd-sourced (yea! The people know best) system is a a classic IoT service, because it combines:

  • a device: the TellSpec scanner, which is small enough to go on a key chain — and would have been impossible without the revolution in sensors and nanotechnology (specifically, nanophotonics): its guts are a low-power laser and a spectrometer on a chip that measures the reflected light, analyzing any food’s chemical composition in less than 20 seconds. This kind of analysis used to require a bulky, stationary spectrometer.
  • analysis in the cloud: the data is transmitted to the cloud, where an algorithm analyzes the spectrum information. As you can imagine, doing this kind of analysis on a large scale and in real time was impossible until the cloud.
  • the app: within seconds, you get an easy-to-understand message that details the food’s components, such as transfats, caloric content, allergens, etc.

How cool is that?

The system is in prototype right now. They’re taking pre-orders now, for delivery in August. The scanner plus a year of the analysis support will be $320, and after that, it will cost $7.99 per month or $69.99 yearly. My normally acceptable range of cost for an app is $.00 or less, LOL, but even a cheapskate like me realizes that this is well worth the price.

What a marvelous invention, and what a proof of concept!

As always, I’m indebted to Postscapes for the tip on this one.

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Calculating Internet of Things ROI — important tool

Posted on 3rd December 2013 in design, Internet of Things, M2M, maintenance, management, marketing, Uncategorized

Just came across this video while researching how to calculate ROI on Internet of Things investments for the e-book I’m writing, and felt compelled to share it.

That’s because it may be hard to calculate ROI fully and accurately for IoT investments if you aren’t thinking in terms of what my friend/patron Eric Bonabeau always pounds into my head: what can you do now that you couldn’t do before?

In the case of the IoT, there are  several things, such as “predictive maintenance,” that weren’t possible before and thus we don’t automatically think of calculating these benefits. It will require a conscious change in figuring ROI to account for them.

According to Axeda CMO Bill Zujewski, there are 6 levels of M2M/IoT implementation, and there are both cost savings and revenue enhancements as you move up the curve:

  1. Unconnected: this is where most firms are today. No M2M/IoT investments.
  2. Connected, pulling data for future use: No return yet.
  3. Service: the investment begins to pay off, primarily because of lower service costs.
    1. Cost reductions:
      1. fewer repair visits  Now that you’re harvesting real-time information about products’ condition, you may be able to optimize operating conditions remotely.
      2. first-time fix rate increases: Now you may know what the problem is before you leave, and can also take the proper replacement parts.
      3. reduced call length: You may know the problem in advance, rather than having to tinker once you’re there to discover it.
    2. Higher Revenues:
      1. Greater customer satisfaction. Customer doesn’t have to pay as much for repairs, down-time is reduced.
  4. Analyze: Putting data into BI and other analysis tools to get greater insights. For example, understand what are bad parts, when they’re failing.
    1. Cost reductions:
      1. fewer service visits: instead of monthly service you may be able to switch to quarterly.
      2. lowering returns
      3. improve product design
    2. Higher Revenues:
      1. Increase product up-time: due to better design and more effective maintenance, longer mean-time-to-failure.
  5. Data integration: begin to integrate data with business processes.
    1. Cost reductions:
      1. warrantees (especially for industrial equipment): fewer claims if you can monitor equipment’s operations, warn owner if they’re using it improperly.
      2. recalls: reduced.
    2. Higher revenues:
      1. pay-as-you-go leases: as we’ve discussed earlier, you may be able to increase revenues by leasing products based on how much the customer actually uses them (which you can now document), rather than selling them.
      2. increased sales of consumables: you’ll be able to know exactly when the customer needs them.
  6. Reinvent the customer experience: According to Zujewski, this is where you “put machine data into the end users’ hands” through a smartphone app, for example, that gives them access to the information.
    1. Cost reductions:
      1. reduced calls to call center: the end user will be able to initiate service and troubleshoot themselves.
    2. Higher revenues:
      1. increases sales: your product will be enhanced, leading to more successful sales calls. You also may be able to charge for some of the new data access services that make the product better.

Zujewski concludes by saying that all of these changes combine into 4 major benefits:

  1. world-class service
  2. business insights (such as better understanding of how your customers are using your products) from all the data and analysis
  3. improve business processes: integrating data allows you to improve the way you perform current processes
  4. highly-differentiated offering due to to the apps and information you can provide users. “You end up demo-ing your apps vs. just the machines”

I was really impressed with this presentation, and it makes sense to me as a framework for calculating ROI on Internet of Things investments (I want to think about other benefits of the IoT that were impossible before to see if there are any other factors that should also be calculated).

I’d be really interested in your reaction: is this a valid methodology? what other factors would you also include?

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