10
Aug
17

IIoT and the Application of Technology

IIoT, or the Industrial subset of the IoT (Internet of Things), has been making a lot of hay around the technology circles over the past year amongst my friends or at industry events. Everyone seems to think they are the ideal technology to “help” the IoT surge that’s upon us.

After a number of meetings with IoT company executives, I was wondering if it really needed anything new (technology wise) or not.  Most of the people I spoke with were relating to very small amounts of sensor data or very few sensors (it’s actually funny when 1000’s of sensors can be “a few”).  Any relatively modest single computer could handle these environments locally, or passing the data back to a centralized datacenter did not induce to much latency in getting an answer or applying new “knowledge”, so, everyone can answer the need of the low end IoT, but, is it a need at this point?

Then came the real meetings…  Meetings with the people equipping “warfighters”, be they boots on the ground or geeks behind a keyboard. I really began learning the absolute benefit to knowledge acquisition, and acting on that knowledge to either make something better (such as the IIoT would want), save or make money (as in a banking example where nanoseconds matter in a HUGE way), or shortening a killchain (saving soldiers’ lives or eliminating bad guys, sometimes achieving both those goals). These volumes of sensor data and the velocity at which they are coming in is extremely important, and will be key points of an upcoming blog.

Discussing these warfighters, reminded me that some equipment (such as the F35, a single seat stealthy muli-role fighter, built by Lockheed Martin for the US Military) are perfect examples of a sensor aggregation and dispersing tool that is invaluable to soldiers. This enables soldiers’ to complete their mission better, faster and more effectively, exactly what the industrial world wants and needs, especially in a global economy.

I was privy to a conversation an advisor of ours (who works at GE) had with another board member.  The discussion was about GE engine sensor data, and how you could predictively service those engines based on that sensor data, thus reducing failures and lengthening flight time.  I started looking at the sensor data from the new Boeing 787 and other IoAT (Internet of Aviation Things) and it really resonated that a new platform may be needed to actually process this massive amount of data. Rethinking of how and where we process Industrial data so that we can get those answers quicker, and apply them where we will see the most savings are where companies can make the most money, quickest.

Imagine that a 787 airframe can generate 844TB of data in a 12 hour flight.  It’s not practical to send that data anywhere “in-flight”, and getting that data from any of the 1000’s of airports it can land at to some central processing center is not practical over the wire.  (Is Fedex really the best option? It might be the only option now…).  Enter edge computing where processing of key sensor data in the field, or at “the edge” where it is actually generated, means you now only move the pertinent results over the wire to a central location.  This speeds up access to that data and answers to questions of in flight stability, and when maintenance should be done.  This is not limited to airlines, but in other sectors like a company drilling for gas or oil, when should one buy or sell a given stock, or (from the military) should we invade a given complex now or get more resources. Processing at the “edge” of sensor data, gives you a much needed speed advantage in any given sector.

Edge computing has been discussed more in the last couple of years, and it may seem like a re-application of consolidation at a different point in data processing.  However, with the unprecedented amount of data from sensors in the IIoT, technology like Axellio from X-IO truly could be a game changer in how we ingest and process that sensor data.  This enables the industrial arm to learn, adapt, and morph based on the new answers obtained from an ever-increasing sea of sensors embedded in everything around us.

 

Keep an eye on the Edge.  It does seem to be growing rapidly and IIoT, IoT, and the like will push it to the limits.

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