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.

IoT Essential Truths: Just Because You Can Do It Doesn’t Mean You Should

Posted on 9th December 2013 in Essential Truths

Whilst (aren’t I the Anglophile?) walking the dog this morning, the “social sensing badges” that I’d slammed a while ago as crossing my personal line in terms of invasion of privacy popped into my head.

As I thought more about these monitors of your personal interactions in the workplace, I thought that one of my comments about them deserved elevation to the level of one of my “Essential Truths” about the IoT (i.e., such basic principles that they should be considered throughout the design and launch of any IoT service):

Just because you can do it doesn’t mean you should do it!

Primarily, it seems to me this adds a crucial ethical component to the IoT, which should never be far from our thoughts because of the omnipresent issues of privacy and security that pervade so many IoT services. In the case of the “social sensing badges,” Sociometric Solutions paints a strong case for how their badges can lead to a more productive workplace, but, IMHO, that fails to outweigh the omnipresent invasion of workers’ personal privacy that the badges represent, especially in today’s poisonous workplace environment (that’s my judgment: love the humane workplaces that prove me wrong!).

Medical solutions should particularly be subject to this test, because the information they gather and diffuse is so personal and potentially harmful. I am a huge fan of these solutions — many can literally save your life, while most will improve your quality of life — but I think they carry with them the need to place heavy emphasis on privacy and security protections if they are to be introduced.

And there’s a corollary to this Essential Truth that companies need to keep in mind:

Just because you can do it doesn’t mean I have to buy it!

That one comes to mind every time I read a breathless new update on the IoT’s Holy Grail. I speak, of course, of the “smart refrigerator!” I’ll grant you that each iteration does add more services, but suffice it to say that I ain’t making a down-payment on any of those on the market, and I doubt whether I ever will!  Why? I don’t buy a lot of prepared refrigerated foods, and I’m making at least a half-hearted effort to eat locally and farther down the food chain. Veggies and grains from the bulk bins at my store don’t come with bar codes, so I can’t personally see paying a premium for a fridge that really isn’t going to fulfill the promise of monitoring my food intake and generating my shopping list. If you’re contemplating a new IoT solution, make sure it’s really worthwhile, vs. just a gimmick.

I’m not sure where I stand on the issue of whether a new technology is essentially good or evil (except for the A-bomb…) or whether it’s ethically neutral.  However, I do think that the IoT, by virtue of its great strength of generating such high volumes of real-time data, does continually bump up against ethical questions, so it’s just smart policy to constantly think of whether you should do it just because you can.

What do you think? I’d love your thoughts on this important issue!

Calculating Internet of Things ROI — important tool

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?