Newsletter Insert July 2016

Drew’s Young Gun Automation Insert

Drew Baryenbruch

What Happens When Technology Makes IoT as We Know it Irrelevant?

On May 25th Joanna Stern of the Wall Street Journal wrote the satiric piece, Smart Tampon? The Internet of Every Single Thing Must be Stopped. Stern describes that the falling price of parts (chips) and the popularity of crowdfunding in the tech space is creating an IoT boom. Yet most of the products are half hatched and most fail to efficiently solve a real problem. From feminine products, to egg trays, detergent ordering buttons, and a pile of pedometer variants, most consumer IoT products are a fad and novelty. At best the majority are inefficient ways to provide a benefit. I agree with Stern and it got me thinking about the future.

Are We Emulating the Most Complex Machine We Know Incorrectly?
The current version of IoT (and most automation systems for that matter) is a loose emulation of the human body. You have a brain (HMI/controller/head end), nerves (sensors), and organs (devices). These pieces work together for some common outcome. This model emulates the internal system of a body. A network like the nerves in your body must connect each input natively. That’s fine for many things but it fails to interact outside of itself. Why not instead model how the human body interacts with the world around us. Emulating our interaction with the world seems far more valuable.

Fig 1.A.I Drew-Drone - patent pending
Fig 1.A.I Drew-Drone – patent pending

What if instead of putting a chip in everything you encounter throughout the day, you create a device that could sense the world as you do with sight, sound, touch, smell, even taste. Something like Jarvis is to Tony Stark, or an intelligent Tinker Bell to Peter Pan. What I really want is an Amazon Echo affixed to a drone with a vision system. With that flying companion I could completely diminish the value of most IoT devices in commercial applications. Plus, how cool would that be!?

Simplicity and Efficiency
The mobility technology is present and evolving with drones. IBM’s Watson won Jeopardy 5 years ago marking a huge milestone with its ability to learn and reference data. The only substantial technical hurdle to over come are vision and battery technology.

Turning what we see around us into actionable data is really hard. Just look around your desk and try to comprehend how you would design a system that could identify just the objects on your desk. Shapes, colors, logos, and writing all compile to reference a classification that will identify an object. That’s very easy for our brains but is an extremely big challenge for a machine. The technology is evolving, but it’s processor intensive which means energy intensive- leading us to the second problem.

Energy storage technology has a ways to go. While a device can be smart enough to recharge itself, Roomba vacuums now do this, you still have to facilitate flight long enough to be useful. High storage, low weight. The paradox of energy storage.

We aren’t there yet, but the beauty of embracing the IoT consumer market is that there is sizable incentive. The consumer market is a massive market and this model is fundamentally more efficient than putting technology into every object a person interacts with.

One interface, one password, one piece of hardware to maintain any aspects of your life you deem worthy. Yes, please.

What About the IIoT?
Is a mobile AI going to replace automated manufacturing lines? Absolutely not, the devices in IIoT provide real value and can afford to be very specialized. A machine is an assembly line; each IIoT device is another work station adding value. It’s not practical to emulate the performance of an assembly line with a single mobile AI subordinate.

I do, however, think there is a place for these devices in many applications.

Walmart has plans to have barcode scanning drones flying through their warehouse within the year. Inventory management and process diagnostics seems like a perfect fit.

In a building automation application a cycling drone could measure environmental data, occupancy and lighting levels. They could also add the benefit to emergency notification services identifying people in medical emergencies and could add another level of security. All without the burden of adding multiple sensors into each room.

Where Do I Sign?
This all may seem a bit science fiction, but with driverless cars scheduled to hit American roads by 2018 can a floating assistant be that far behind? I sure hope not.

What are you thoughts?




March Survey Results:

The survey results continue to fascinate and entertain me. While responses are confidential I’d like to send a shout out to respondents Phil McCracken and Hugh Jass. Proof I’m not only person in this industry with a firm appreciation for adolescent humor!

Behind the Numbers:

  • The 11.54% of respondents who said they used “other” PLCs most were primarily building automation users. A host of building automation controllers were mentioned.
  • To the single respondent who admitted they are at work a lot but don’t get much done – we salute you. Your secret and identity is safe with us.
  • We issued our first ever open ended survey question “The thing I hate most about PLCs is:”. Most of the gripe revolved around cost, programming limitation, training or limited processing/memory.
  • With the “Who Shot First?” question we offered the ability to comment. We didn’t ask for comments or explain what to comment on. The option was simply available. Nearly 25% of respondents took advantage of the opportunity. Here are a few of my favorite responses:

  • If at first you don’t succeed, admit it, you are a loser.
  • WTF kind of question is this LOL I like it!!
  • Thanks for the reliable serial modules, working with other products makes me feel like Scott Sterling sometimes, he’s a brilliant soccer and volleyball player but it doesn’t seem to end well for the guy.


Which PLCs do you work with most?

  • Allen-Bradley – 58.46%
  • Siemens – 6.92%
  • Beckhoff – 0.77%
  • PC Based Control – 3.08%
  • A Mix – 18.46%
  • Other – 11.54%

In a typical week I work:

  • 40 or less hours – 13.18%
  • 41-60 hours – 79.84%
  • 61-80 hours – 4.65%
  • More than 80 hours – 1.55%
  • I’m there a lot but don’t get much done – 0.78%

Keeping obsolete controllers running is:

  • Not Very Important – 14.62%
  • Somewhat Important – 35.38%
  • Very Important – 35.38%
  • Critically Important – 14.62%

Who shot first?

  • Han Solo – 47.2%
  • Greedo – 10.40%
  • I’m thankful George
    Lucas can’t change it again! – 42.4%