Live-blogging @ Wearables + Things

Posted on 20th October 2014 in design, health, Internet of Things, m-health, mobile, Quantified Self, wearables

 

Just arrived @ Wearables + Things conference (I’ll speak on “Smart Aging” tomorrow). Hmm: there’s one noteworthy player absent from the conference: those guys from Cupertino. Wonder why they’re not there (perhaps in stealth mode??)

Conference already underway, about to have 2 new product reveals!

  1. iStrategyLabs, “Dorothy,” connects your shoe to your phone. You’re stuck in a conversation, need way to leave. What if you could click your heels together three times (get it, Dorothy???) and you’d get a bail-out call (or you can trigger an IFTTT recipe or call for a pizza…). “Ruby” goes in shoe.  OK, this ain’t as significant as either the Lechal haptic shoe, but who knows how it might evolve…
  2. Atlas Wearables’ fitness product, Atlas. Their goals is seamless, frictionless experiences. “What if device could recognize specific motions you’re making?” This is really cool: it recognizes and records a wide range of fitness activities, such as push-ups.  I really don’t like fact that my Jawbone can’t do that, so this looks good!

Sony Mobile, Kristian Tarnhed. Challenges:

  1. g data overload. They have a “lifelog” app that tries to make sense of all the data.
  2. too many devices that want your attention. Make them complement smart phone as much as possible.
  3. is it really wearable, usable? 

Very funny: no one mentions Apple. 10-ton gorilla in the room????

Amazing preso by Jim McKeeth: “Is Thought the Future of Wearable Input?”  Guy wearing Google Glass is controlling a drone! Wouldn’t that be an incredible thing for “Smart Aging”  to allow a frail elder to control various household things just by thinking them?

 

Oren Michels, chief strategist, Intel (he was an API pioneer at Mashery):

  • APIs make connections. The Epocrates platform from Athena Health is an example: may save $3.5B.
  • Also working in travel. Example is Sabre, which has switched to an open API.
  • APIs create better customer experiences: Apple Pay! 30% of Starbucks revenue from its phone purchase app.

Quick time to market: Coke was able to restock vending machines instantly during 2012 Olympics through API.

  • Examples:
    • better healthcare monitoring: give small devices processing power through cloud
    • connected car ecosystem (BMW iConnected Services, MyCityWay, TomTom’s WebFleet)
    • Snapshot from Progressive
    • Inrix — “data for planning smart cities”

This, IMHO, is sooo important: open APIs are great example of my Essential Truth of “who else can use this data?” — you don’t have to develop every kewl use for your device yourself: open the API and others will help!

Peter Li, Atlas Wearables (the company that debuted their new device yesterday):

  • iPhone: remember, it was a 3-in-one solution.
  • sensors now commoditized: cheap & tiny
  • he was a biomedical engineer
  • synergistic benefits by combining data streams
  • era of augmentation: making you better without you having to think about it.
  • frictionless actions

“sensors root of the revolution”

Brad Wilkins, Nike science director:

  • he’s exercise physiologist
  • they have whole detailed process to understand physiological phenomena. Role of sensor is the describe the phenomena. Then apply that data to enhance athlete potential

Noble Ackerson, Lynxfit, “Hacking Your Way Through Rehab With Wearables”

  • they let content publishers (they work with Stanford Health, UnderArmour, etc.) in rehab area to push info to devices. Prescribe workouts.  Device agnostic.
  • They’ve imported 65 different activities into program.
  • Track: heart rate, pace, position, speed, endurance, breathing, sentiment.

Panel: Jim Kohlenberger, JK Strategies; Jose Garcia, Samsung; Mark Hanson, BeClose; Alison Remsen, Mobile Future:

  • BeClose is working with seniors!!
  • Samsung working with airports to make flying experience more enjoyable.
  • BeClose: take some of burden off health care system.
  • how government can help: faster networks. “First, do no harm.” — Digital Hypocratic Oath.

DHS (sorry, didn’t get his name):

  • In a crisis,  “data  must inform at the speed of thought” Brilliant
  • To be operational, data must be intuitive, instinctive, interoperable, and wearable.
  • Creating “Next Generation First Responder”
  • Creating fire jackets with sensors built in.

Proximity-aware apps using iBeacon:

  • beacons are Bluetooth v4.0 Low Energy transmitters.
  • mobiles can identify and determine proximity to beacon: usual range is 25 to 40 m, but you can tune it to much shorter range.
  • beacons broadcast unique identifier for the place. Also provide Measured Power Value: what’s signal strength of beacon at specific distance.
  • the beacon only sends out a unique identifier, which triggers the app contains all the info that drives the experience.
  • app is notified whether you’re in immediate range, near, or far range (might even want to present content when person exits the area).
  • beacons protect privacy by being opt-in. They are transmit only: don’t receive or collect signals from mobile devices.
  • Apple requires that the app specifically ask user to allow proximity-aware mobile app to access their location.
  • non iBeacon versions: AltBeacon (Radius Network’s opsolves en source alternative), and other ones that specific companies will introduce, optimized for their products.
  • Radius multi-beacon: solves fragmentation problem or multiple, incompatible beacon ad types. Their RadBeacons handle both types.
  • RadBeacon: USB powered, coin-cell battery powered, AA battery powered.  Most beacons will only last about a month before battery change.
  • Future of beacons: will be split in market: corporate (one of their questions has rolled out more than 16,000 — they won’t powered or long-battery-life versions & remote monitoring) vs. consumers (cheap & disposable). Will be integrated into equipment (wifi access-point hotspots, POS terminals, fuel dispensers, self-service kiosks.

My presentation about “Smart Aging”

 

Privacy & Security Panel:

  • There is real risk of personal data being intercepted. “No perfect solutions.”
  • Data can be stored on smart phone OR uploaded to cloud. What control does user have? What if you have health wearable that sends info on blood pressure, etc., to cloud, where it gets shared with companies, and, for example, it can link data to your Facebook data, could be risk of disclosure.
  • HIPPA and variety of other regulations can come into play.
  • Things moving very quickly, data captured & used. Example of Jawbone data from people who were sleeping during California quake: users upset because the data was disclosed to news media — even though it was just aggregated, was creepy!
  • FTC went after the Android flashlight app that was aggregating data. A no-no.
  • have to make it simple to understand in statements about how your data will be collected & used.
  • Tiles: if the device is gone from home, will send alert to ALL Tile devices. You might be able to modify the software so you (bad guy) could retrieve it it while the owner would think it was still lost.  Stalker might even be able to use this data..

Scott Amyx, Amyx & McKinsey,  “The Internet of Things Will Disrupt Everything”:

  • Example of McLean, the developer of intermodal shipping container. Hmm: does Amyx know about how Freight Farms has created IoT-enhanced food growing in freight containers???
  • future of M2M will allow sensors with embedded processors — smarter than today’s computers.
  • memory: over time, memory will only grow.
  • wifi: most locked networks are idle most of day. Harness them.
  • lifi: 2-way network to turn any light as a network. Higher-speed than wifi.
  • mesh networks (long-time fascination of mine, especially in disasters): every node creates more powerful network. Can’t be controlled by a central gov.
  • Implications:
    • can disrupt telecom (mesh networks)
    • shifting consumer data from cloud to you
  • they’re testing a system that would tell what a person really feels while they’re in store, film companies can test from pilot whether people will really like it. Creepy??
  • working with Element to bring this to fashion show: would gauge reaction.
  • IoT won’t be great leap, but gradual trend (like my argument that companies should begin with IoT by using it to optimize current manufacturing).
  • incredible vision of how you’ll drive to a biz appt. in driverless car, you’ll get briefing on the meeting from your windshield.
  • opportunities at every stage of the IoT development shift.
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Why the Internet of Things Will Bring Fundamental Change “What Can You Do Now That You Couldn’t Do Before?”

Posted on 12th August 2014 in automotive, design, Internet of Things, M2M, maintenance, manufacturing, mobile, paradigm shift, real-time regulation, transportation

The great Eric Bonabeau has chiseled it into my consciousness that the test of whether a new technology really brings about fundamental change is to always ask “What can you do now that you couldn’t do before?”

Tesla Roadster

That’s certainly the case for the Tesla alternative last winter to a costly, time-consuming, and reputation-staining recall  (dunno: I must have been hiding under a rock at the time to have not heard about it).

In reporting the company’s action, Wired‘s story’s subtitle was “best example yet of the Internet of Things?”

I’d have to agree it was.

Coming at the same time as the godawful Chevy recall that’s still playing out and still dragging down the company, Tesla promptly and decisively response solved another potentially dangerous situation:

 

“‘Not to worry,’ said Tesla, and completed the fix for its 29,222 vehicle owners via software update. What’s more, this wasn’t the first time Tesla has used such updates to enhance the performance of its cars. Last year it changed the suspension settings to give the car more clearance at high speeds, due to issues that had surfaced in certain collisions.”

Think of it: because Tesla has basically converted cars into computers with four wheels, modifying key parts by building in sensors and two-way communications, it has also fundamentally changed its relationship with customers: it can remain in constant contact with them, rather than losing contact between the time the customer drives off the lot and when the customer remembers (hopefully..) to schedule a service appointment, and many modifications that used to require costly and hard-to-install replacement parts now are done with a few lines of code!

Not only can Tesla streamline recalls, but it can even enhance the customer experience after the car is bought: I remember reading somewhere that car companies may start offering customer choice on engine performance: it could offer various software configurations to maximize performance or to maximize fuel savings — and continue to tweak those settings in the future, just as computers get updated operating systems. That’s much like the transformation of many other IoT-enhanced products into services, where the customer may willingly pay more over a long term for a not just a hunk of metal, but also a continuing data stream that will help optimize efficiency and reduce operating costs.

Wired went on to talk about how the engineering/management paradigm shift represented a real change:

  • “In nearly all instances, the main job of the IoT — the reason it ever came to be — is to facilitate removal of non-value add activity from the course of daily life, whether at work or in private. In the case of Tesla, this role is clear. Rather than having the tiresome task of an unplanned trip to the dealer put upon them, Tesla owners can go about their day while the car ‘fixes itself.’
  • Sustainable value – The real challenge for the ‘consumer-facing’ Internet of Things is that applications will always be fighting for a tightly squeezed share of disposable consumer income. The value proposition must provide tangible worth over time. For Tesla, the prospect of getting one’s vehicle fixed without ‘taking it to the shop’ is instantly meaningful for the would-be buyer – and the differentiator only becomes stronger over time as proud new Tesla owners laugh while their friends must continue heading to the dealer to iron out typical bug fixes for a new car. In other words, there is immediate monetary value and technology expands brand differentiation. As for Tesla dealers, they must be delighted to avoid having to make such needling repairs to irritated customers – they can merely enjoy the positive PR halo effect that a paradigm changing event like this creates for the brand – and therefore their businesses.
  • Setting new precedents – Two factors really helped push Tesla’s capability into the news cycle: involvement by NHTSA and the word ‘recall.’ At its issuance, CEO Elon Musk argued that the fix should not technically be a ‘recall’ because the necessary changes did not require customers find time to have the work performed. And, despite Musk’s feather-ruffling remarks over word choice, the stage appears to have been set for bifurcation in the future by the governing bodies. Former NHTSA administrator David Strickland admitted that Musk was ‘partially right’ and that the event could be ‘precedent-setting’ for regulators.”

That’s why I’m convinced that Internet of Things technologies such as sensors and tiny radios may be the easy part of the revolution: the hard part is going to be fundamental management changes that require new thinking and new questions.

What can you do now that you couldn’t do before??

BTW: Musk’s argument that its software upgrade shouldn’t be considered a traditional “recall” meshes nicely with my call for IoT-based “real-time regulation.”  As I wrote, it’s a win-win, because the same data that could be used for enforcement can also be used to enhance the product and its performance:

  • “by installing the sensors and monitoring them all the time (typically, only the exceptions to the norm would be reported, to reduce data processing and required attention to the data) the company would be able to optimize production and distribution all the time (see my piece on ‘precision manufacturing’).
  • repair costs would be lower: “predictive maintenance” based on real-time information on equipment’s status is cheaper than emergency repairs. the public interest would be protected, because many situations that have resulted in disasters in the past would instead be avoided, or at least minimized.
  • the cost of regulation would be reduced while its effectiveness would be increased: at present, we must rely on insufficient numbers of inspectors who make infrequent visits: catching a violation is largely a matter of luck. Instead, the inspectors could monitor the real-time data and intervene instantly– hopefully in time to avoid an incident. “
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In case you missed it, great panel today on the IoT and government

Posted on 19th March 2014 in government, Internet of Things, US government

In case you missed it, old friend Christopher Dorobek put together a great (in all modesty, LOL …) panel today for his “DorobekINSIDER” series on GovLoop about how the Internet of Things will transform government.  I’ll try to summarize it in a later post, but you can listen in here!

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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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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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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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Best quick intro to the IoT that I’ve seen!

Posted on 18th November 2013 in agriculture, automotive, design, energy, environmental, government, health, home automation, Internet of Things, M2M, mobile, transportation

Following up on my last post, I’ve found what I think is the best quick intro to the Internet of Things!

“Internet of Things,” released today by the Center for Data Innovation (hadn’t heard of them! BTW, they also get points in my book for covering XBRL, the magic potion for data…) is a quick read: it has short intros to most of the major consumer-oriented areas affected by the IoT, from healthcare to home automation, combined with two examples for each of those topics. I hadn’t heard of some of the examples (thanks, authors Daniel Castro and Jordan Misra!), although most are frequently cited ones ranging from the Nest thermostat to the Vitality GlowCap.  All in all, they’ll show almost any skeptic that the IoT is already a reality and that it will change their life!

The report concludes with brief policy recommendations for government and business alike:

  • (for government agencies) lead by example, i.e., include funding for sensors in bridge projects, etc. Yea (you listening, Obama Administration?).
  • reduce barriers to data sharing (this harkens back to my Data Dynamite book: data gains value by being shared!).
  • give consumers access to their data (again, something I wrote about in Data Dynamite).
  • avoid inundating consumers with notices (a fine line, since they need to be informed, in plain English, about how their data will be used).
  • regulate the use of data, not the collection (in line with Mercatus Center’s advice)

All in all, a nice intro to the IoT!

BTW: Thanx to ol’ friend Pete O’Dell for turning me on to this report!

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Two good sites if you’re introducing the IoT

Posted on 13th November 2013 in agriculture, cities, energy, environmental, health, home automation, Internet of Things, M2M, manufacturing, marketing, transportation

Categorize this under “posts I’ve been meaning to write for a long time!”

For the current writing assignment I’m working on, I’m looking for as many good examples of practical Internet of Things applications that are available right now.

There are two sites that I repeatedly go to for those examples that deserve some praise.

postscapesOne is Postscapes, which I find to be an important all-around IoT news source. It features products (and links to their sites) in the “Body,” “Home,” “City” and “Industry” categories, as well as a DIY/Open Source grouping. The descriptions are well written and it’s attractive.

The other site is a corporate one, from Libelium, the Spanish open source sensor platform. A portion of its site is devoted to “50 Sensor Applications for a Smarter World,” grouped under “Smart Cities,” “Smart Environment,” “Smart Water,” “Smart Metering,” “Retail,” “Logistics,” “Industrial Control,” “Smart Agriculture,” “Smart Animal Farming,” “Security and Emergencies,” “Domotic and Home Automation,” and “eHealth.” There’s a wealth of accompanying information about — surprise! — the Libelium sensors that are matched to each of these applications. Of course it’s marketing for Libelium, but the range of applications does illustrate the wide range of ways that the IoT is already affecting industry, cities, and personal lives.

Check both sites out — and point your skeptical contacts who wonder if the IoT is just a laboratory curiosity to them!

 

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Smart water grid — as important as smart energy grid

Posted on 5th November 2013 in environmental, Internet of Things, M2M

Environmental efficiency is one of my passions, and there’s compelling evidence that shortages of clean water are almost as much a threat to life on Earth as global warming is.

That’s why I was so excited to learn that Spain — already an exemplar of “smarter cities” thinking (due in large part to Libelium using it as a test site for its devices) — is launching a “smart water grid” program in the city of  Cáceres.

According to Jesse Berst (you really should subscribe to his Smart Grid News!), ACCIONA Agua, the water services division of ACCIONA, a global renewable energy, infrastructure and water services group, will build the system “as part of a European project that aims to apply new technologies to the management of drinking water networks.”

Its benefits will parallel those for “smart grid” electricity projects, including real-time detection of underwater leaks (so they can be repaired more quickly) and real-time control of water distribution and use, and remote meter reading that will allow the utility to alert homeowners to possible leaks in the home or other problems.

Note the critical benefits of real-time data: “Real time data is expected to optimize investment plans according to real needs, as well as hone the management of water services.”

Components will include:

  • remote meter readers
  • GIS
  • remote control information
  • water quality monitoring sensors
  • mathematical model to predicting the system’s behavior.

The project is part of ” SmartWater4Europe, an EU research project that brings together 21 participants, including water utilities, technology companies, universities and research centers. The project has a budget of more than €10 million, of which €2.5 million has been assigned to Cáceres.” Results will be monitored over a 4 year period.

I’ve been noodling for a while about what it will take to get mainstream companies that may not even know about the IoT, let alone have a strategy to capitalize on it, to test the waters. I’ve concluded that since water and energy utility bills are such a big issue for most companies that launching “smart grid” projects that capitalize on utilities’ investments in this area and can lead to quick savings in utility bills might be the ideal entry point. What do you think?

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