The very nature of technology innovation lends itself to the types of buzzwords and jargon that can often impede people’s understanding of the technologies themselves. These buzzwords can be metaphorical but still easy to understand terms such as “cloud” or “Internet of things,” and they also include jargon that can hinder people’s understanding of the technologies themselves.
In IT, we call it a “use case.” Still, that term is essentially a tangible manifestation of the context in which technology will be most effective, whether that’s a manufacturing scenario, a telematics platform, or an IoT integration.
Context is important even within IoT. It can be used in anything from a simple smart thermostat to an advanced MRI machine or any number of other use cases.
Edge computing is not about creating a device but making sure it can transmit and receive data reliably.
People focus on the platform side of the business all too often because that’s where they’re going to see ROI on the data and the analytics. However, all that great back-end processing won’t make much difference if the network edge is not in order.
Edge computing tends to be overlooked because most people simply take it for granted. This happens a lot during the manufacturing process especially, because there’s a mindset that when you buy a device like a laptop or a smartphone, that device is going to communicate with other devices through an interface that’s driven by the user.
Our thinking is: “Use the smartphone to send data directly to your laptop and then use the laptop again to send the same data to your printer.”
If a device is meant to be self-sustaining, it can become costly to maintain. We’re not talking about using rolling trucks to troubleshoot routers. These devices can be buried alongside crops to measure soil moisture.
We are creating small-footprint, autonomous devices in the Internet of things world. Most of our initial interactions with customers and business partners revolve around the question, “How can we connect to this thing?” What can we do about this protocol? What can we do to support this sensor?
The most difficult challenges come when we get to the electronics level, and begin to figure out how to interface with the first level of the software tier.
In the world of IoT, devices are built with some form of communication standard in mind. However, remembering that the actual data that they transfer – and how they transfer it – is another piece of the puzzle altogether. The devices must be kept in good condition throughout their entire life span.
Perhaps the temperature rose or fell, or perhaps the device is simply periodically intended to send information back to the network to perform some action.
People are often challenged to design these things. This might be their first experience with having to worry about these issues. It’s not as simple as a printer or laptop.
Even something as simple as the data itself – and understanding how modern cellular devices consume data compared to their Wi-Fi and 3G counterparts – can derail an entire IoT project before it even gets off the ground. This is a more difficult world to navigate.
Another key area of that world involves being able to make sure that devices are properly scaled and calibrated, and that the data they transmit is handled in a meaningful way. If a connection goes down, the data must be properly queued to ensure that it is still able to reach its destination when it is restored.
Many otherwise very successful companies have learned these types of lessons the hard way by not taking into account how their devices would behave in the real world. They might test the devices in a laboratory when they are ultimately intended to use cellular data.
This critical communication function is so expensive that the device becomes unviable from a business perspective.
Is the first job or function the device is supposed to do? Will it perform as expected?
It can also be disastrous if developers spend too much time focusing on the device’s functionality before spending enough time figuring out if the physical device is going to function.
Whether it’s some kind of simple telematics device for a vehicle, an advanced module for use in manufacturing, or any number of devices in between, the all-important work of making sure that a given device and its components will work the way it’s intended is often relegated to the people with the least experience.
In many cases, people get thrown into it, and they don’t appreciate the complexity they’re dealing with until they’ve already suffered any number of setbacks. You could have an environmental problem, battery life issues, or something simple like where the antenna should be placed. How will it be updated once it is in the field?
These types of devices can fail once they have been placed in the field. The cost of replacing them and reshipping them individually can cause a complete product line to collapse. It is important to test them in the field with smaller groups, and not let the garden path lead you to scale them up too fast.
While grand plans are wonderful, starting small and iterating over the long term is the best way to prevent problems.
Edge computing is often referred to as the “Last mile” technology. It is, in fact, the most difficult of all.
Large telecom and IT companies have always called the connection to a device or edge the “Last Mile”, as in delivering data services from curb to house.
This is a false view of IoT. The device is the source of all data. Therefore, connecting to the device and delivering data to the application infrastructure is crossing the “First Mile.”
Regardless of what, once we understand and can put into context how edge computing works in the real world, it is possible to see the finish line.
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