Foggy Meaning Around IoT
In less than 5 minutes of reading about the Internet of Things, words like “edge, “fog” and “cloud” will crop up. This confuses people. Why talk about network terms? Isn’t IoT supposed to be about the “things?”
Here is a quick way to cut through the fog of meaning.
Internet of Things (IoT) is about things. Industrial IoT (IIoT) is very much about things. But we must get data from those things. And we must take actions. Some of the actions are related to the things.
So, yes, we do need to think about networking. We did see the word “Internet” after all.
But, most of the firms pushing Edge, Fog, or Cloud aren’t focused on the “things” or your “actions.” They are focused on the network and processing. They want to sell stuff.
They want to sell: Connectivity, bandwidth, backhaul, storage, and/or computing. Those may be needed to create a solution. But they are just the IT components of a solution. None of them are a solution.
When someone tries to tell you Cloud is better than Fog, it means they are selling Cloud storage, Cloud computing, or both. It does not mean they actually understand what you need for your IIoT solution.
What if it’s not about edge, fog, or cloud? What if IIoT is about operational value?
At Lone Star, we’ve done a lot of writing about Edge solutions. That’s because we see it as the most misunderstood IIoT topic. But we are agnostic about where analytics should be done. We’ve invested to ensure solutions we create can run anywhere.
We call this “the point of need.” Delivering insight at the point of need is a clear path to creating operational value. We think IIoT should have a very large ROA (Return on Analytics). We also think the ROA should be targeted.
If you want to cut through the fog of meaning, refuse to use the terms from consumer networking and corporate IT. Think about IIoT in terms of your operational needs. And, think about your point of need.
To do this, we suggest five levels of IIoT solutions.
Asset Level – Some solutions must deal with a single asset. This may be driven by lack of reliable network connections. It might stem from the need for air-gapped security. It may be rooted in an asset’s mobility. Examples include Electric Submersible Pumps two miles underground in an oil well, the complex transmissions in helicopters, and some railroad applications.
Local Level – Some solutions support a group of associated assets, which are close to each other. These may be somewhat independent, or may be a system of systems. Examples include an oil production pad with several production systems. Another example might be all the electric motors in a factory.
Regional or Sub-Functional Level – In some cases, IIoT must support a portion of a corporate function, such as material handling systems. MHS is a subset of distribution, so it’s not an entire corporate function, but it deserves treatment as a distinct thing in many cases. A regional aggregation might be all the production wells in an oil field, and all the support functions for the field.
National or Functional Level – Some IIoT applications requite centralized aggregation on a significant scale. Examples here include all the rolling assets of a fleet within national borders. Retail distribution systems are another example. Centralized oversight of multiple offshore oil platforms would fall into this category in most cases.
Global Level – We reach this level when we need to look across the world, across the entire corporation, or both. Airline operations are an example in this category.
We suggest that IIoT discussions include this kind of thinking before moving to network architectures. Form should follow function. So, think about the kinds of operational opportunities you want from IIoT, and how they might map into this five-level framework.
Next think about how to start. Can you get some early wins at the asset or local level?
Then think about the initial solution architecture. You may not need to think about the long-term architecture to get started.
After that, you can listen to solution salesmen who want to pitch the kind of solution they are pushing.
But please remember, at Lone Star we don’t care if it’s the edge, fog, or the cloud. We provide analytic insights at the point of need.
About Lone Star Analysis
Lone Star Analysis enables customers to make insightful decisions faster than their competitors. We are a predictive guide bridging the gap between data and action. Prescient insights support confident decisions for customers in Oil & Gas, Transportation & Logistics, Industrial Products & Services, Aerospace & Defense, and the Public Sector.
Lone Star delivers fast time to value supporting customers planning and on-going management needs. Utilizing our TruNavigator® software platform, Lone Star brings proven modeling tools and analysis that improve customers top line, by winning more business, and improve the bottom line, by quickly enabling operational efficiency, cost reduction, and performance improvement. Our trusted AnalyticsOSSM software solutions support our customers real-time predictive analytics needs when continuous operational performance optimization, cost minimization, safety improvement, and risk reduction are important.
Headquartered in Dallas, Texas, Lone Star is found on the web at http://www.Lone-Star.com.