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How to determine the top IoT usage and data industries for 2020

If you’ve seen the film Casablanca, you’ll remember one of the final scenes where Captain Louis Renault turns to Rick Blaine and says, “round up the usual suspects.” As we head into 2020, the mystery of which industries will show the greatest penetration of IoT usage and value begins to unfold. However, this question has popped up annually for the last decade, and with several analyst firms and magazines publishing overlapping lists, it’s easy to round up the usual suspects: manufacturing, healthcare, and transportation and logistics. Or is it smart cities, retail, and media and entertainment? How do you actually decide?

Defining the usual suspects

Let’s examine what rounding up the usual suspects means. To determine these top industries, we want to look at the characteristics or traits that warrant something being a great application for IoT and the need for data at the edge. Based on my previous experience as an embedded systems engineer, I believe the answer boils down to business and technical virtual teams asking themselves the following questions and generating clear, positive answers to them:

  • Will the investment in IoT quantitatively reduce my costs or enable me to generate more revenue?
  • Can I model out my edge in a way that enables me to identify how applications of IoT with associated intelligence at this edge will generate positive outcomes for the answer to question one?
  • Can I apply the appropriate process orchestration, rules and exception handling, and supporting data processing and analytics to implement or improve automation, machine-to-machine interface and decision support in real-time to what I’ve modeled in the answer to question two?
  • Can I implement the infrastructure necessary, such as 5G networks, edge data management, bolt-on intelligence to brown-field environments and implementation of select machine learning inference models out at the edge to support a portfolio of projects addressing the answer to question three?

Identifying the usual suspects

If you can create positive workable answers to all four of these questions, you are ready to line up your suspects for positive ID by the eyewitness. In other words, look for the right IoT projects in the right industries. I would argue that you should look for the following:

  • Real-time edge decisions and actions. These decisions can make or break your business. For example, prescription drug packaging, product defects on an assembly line, package routing on a conveyor belt, and many others.
  • Remote field environments. This is where bandwidth for connection to the cloud or other centralized IT resources is at a premium, or those connections experience periodic disconnection either unexpectedly or by design that are core to your business, such as airline flight services, transoceanic cargo shipping, certain defense and intelligence cases.
  • Local data processing. Additional processing of IoT devices and the data they generate by software that leverages resident software containing artificial intelligence, which can then be applied in an evolutionary, iterative way across multiple projects. For example, condition monitoring leading to preventative maintenance, then turning into predictive maintenance that allows for the same data and underlying infrastructure to support digital twinning.

With this methodology, you can make your own predictions as to which industries have the greatest application of IoT devices and data at the edge. For me, the manufacturing industry tops the list for 2020.

However, it’s not all sub-verticals in manufacturing. In fact, I would say Heavy Industry and High-Tech manufacturing. To get even more granular, I’d go with manufacturing that has an Industry 4.0 roadmap towards digital twinning. Similarly, I would say transportation and logistics would be on my list, with a focus on streamlining and accelerating accurate package delivery. With these characteristics in mind, you can then revisit the usual suspects in a more granular and measured fashion.

All IoT Agenda network contributors are responsible for the content and accuracy of their posts. Opinions are of the writers and do not necessarily convey the thoughts of IoT Agenda.

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