The fourth industrial revolution is upon us, commonly referred to as Industry 4.0. The third industrial revolution was the transformation from analog to digital, all the way up to utilizing the Internet and the beginning of cloud computing. The next generation yielded the hybrid approach of edge and cloud computing with everything in between. Most organizations have adopted the cloud, and in doing so have moved away from edge based computing. The problem is that there are numerous cases where cloud only is in fact not the best solution. Being able to make decisions directly on the edge, where things are physically located, is critical for many industries. I say “things” because the Internet of Things (IoT) has become the defacto standard for describing an edge computing solution. It’s a great word, but there are too many possibilities of what could be out on the edge, so many things! This blog will discuss a few industries where edge decision making is critical, and has the ability to immediately enhance overall business operations.  

Before we jump in, I want to quickly discuss the general concept of edge computing and its broader benefits. Today, devices are collecting massive amounts of data and most of us are not sure what to do with it. A lot of times this data is pushed to the cloud for eventual analysis. While most of this data is completely useless, it is still sent through and therefore utilizes network and cloud resources. This method costs more money and has a slower overall response time than if data were to be processed where it is collected- on the edge. The industries discussed here all share one thing in common, the ability for real time decisioning is absolutely crucial. It may be hard to believe, but in many cases, the difference between one second and a couple milliseconds could save lives.  

Let’s look at some industry specific examples…

Automotive

If you know me, you know that I’m a huge car guy so this one is easy for me. There are many places within the automotive industry where edge decision making can be beneficial, but I’m going to focus on autonomous vehicles. This one is fairly obvious to think about. Do you really want to rely on an external connection while sitting in a car that’s driving itself? Absolutely not. Everything should happen onboard. Collision detection, pedestrian detection, lane departure detection, and driver monitoring, to name a few, cannot afford to depend on external decision making. Instead they must depend on an edge solution to make real-time decisions. I will point out that the automotive industry is ahead of the curve on this for in-vehicle solutions. They have been building computers into vehicles for years now. We already recognize the benefits of using an edge computing solution in vehicles, now it’s time for other industries to jump on the bandwagon.

Telecommunications

This one may seem unintuitive because the telecommunications industry should have the best access to vast networks and high-speed data transfer between edge to cloud, but sometimes that’s not the best solution. I’m not a networking expert, but in speaking with enough people who are, I realize that what goes on behind the scenes to keep the backbone of the Internet up and running is quite complicated to say the least. There are buildings around the world contributing to keeping the lights on. Adding computing power to the existing infrastructure enables us to distribute processing load across these facilities, creating an edge solution. For example, utilizing an edge database in each facility for real-time decisioning on data flow, or anything else, means traffic can get where it’s going faster and cheaper. This eliminates the need for over utilizing a network when it’s not necessary.

Mining

The case for mining is a bit different than the others. The conversations I’ve had with mining professionals indicate that at the moment, there is not a ton of analytics or data monitoring happening with most of their machinery. Typically these operations are still quite analog. This works, but you cannot operate at, or even near, peak efficiency if you don’t really know what’s going on. Or maybe you can if you’re lucky, but that’s inconsistent. Adding an edge computing solution directly to machinery provides the platform for next generation analytics. The first step is setting up data collection on various machinery, this is the foundation required for data scientists to be able to analyze data and identify patterns for optimal performance. This analysis typically takes place in a central location, but once the models are created they can be applied directly to IoT edge devices running locally on each individual machine. Adding operator feedback, even as simple as LED lights, can provide real results instantaneously.

Why the Edge Solution?

If you’ve read this far you may have realized that I’ve said the same thing three times. Pushing decision making to the edge in a distributed system provides key results better, faster, and cheaper. Truthfully, this solution is industry agnostic and the concept applies practically everywhere. Removing full reliance on the cloud is a necessary next step in the fourth industrial revolution. A key building block in these solutions is an edge database, like HarperDB. In fact, we’re the only database in the world that can run the same code base both on the edge and on the enterprise. Give us a try today…

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