Last week, I wrote about the first five of Rich Quinnell’s “10 Top Challenges Industrial IoT Must Overcome in 2015,” which appeared in EE Times in late December. Here’s a summary of the remaining challenges on this list.
Device management was the sixth challenge, with Rich relying largely on a quote to make his point:
“‘Intelligent devices usually have limited CPU power, limited memory, and limited disk space,'” says David Beberman, vice president of marketing at Aicas. ‘The technical challenge is to enable intelligent devices with the ability to be securely reconfigured and reprogrammed in large distributed systems within their resource limits, in a stable, resilient manner. Most intelligent devices have limited or no reconfiguration or reprogrammability capabilities. This limits the ability to push computation to the “edge” of the network and thus the ability to realize a flexible dynamic IIoT.'”
Power efficiency is something that we’re always keeping an eye on, and with more and more bells and whistles (like our MitySoMs!) embedded in IIoT applications, power consumption will be of increasing importance. Power efficiency is not just a challenge for individual devices, but with so many IIoT devices coming on board – think Carl Sagan here – power consumption is going to be a critical factor across the entire landscape. (Seems like just yesterday we were worrying about the power consumption of hosting providers’ data centers. The coming level of consumption will eclipse that.)
In the article, the assertion is made that the need for a common development environment also presents a challenge to IIoT, with software developers, cloud-based coders, and embedded developers all using different development tools. Rich quotes Mike Kaskowitz of Micrium, who says that:
“’Often, it is difficult for a single person to span this ecosystem, which is driving a need for pre-integrated solutions that deliver an end-to-end portfolio of embedded software, protocol stacks, and cloud services to facilitate the development of IIoT devices.'”
Maybe I’m being too short sighted, but in my view these two worlds are always handled differently. The skills needed to address the real-time nature of embedded applications are far different from those needed in the cloud. I do agree that pre-integrated systems (embedded+cloud) will help organizations deploy IIoT, and are even a requirement. This will allow organizations to avoid having to develop embedded skills in-house. This may be the real point being raised here.
Acquiring talent and expertise is a perennial challenge in the tech world, and the IIoT will only place more demand on developers and on big data analysis gurus. (At Critical Link, we’re fortunate in that there are a number of excellent engineering schools around, and many young engineers – having grown to enjoy the upstate New York lifestyle – want to stay in our area.)
I had never really thought about it, but as we dig into and analyze our business data at Critical Link, I can really see the need in the world for many, many more data analysts in the future!
Somehow, I knew that the list would end with data, and it does, as Rich’s final challenge that IIoT will need to overcome is data diversity:
“…the vast variety of devices, applications, and implementations within the IIoT will result in a massively heterogeneous set of data. This not only includes variation in the format and interpretation of data (Celsius vs Fahrenheit, for instance), but in the quality, frequency, and timing of the data. The IIoT will need to adopt standards or find an algorithmic way of handling such data diversity.”
All I can say is that, with all these challenges, IIoT will have a pretty busy year on its hands.