|By Steve Latham||
|June 9, 2016 06:07 PM EDT|
One of the things that strikes me with many of the applications that we see ramping up around the Internet of Things, is the intense focus on the “sexy” part of the solution, and not so much on the beastly and often complex side of IoT. That’s the part that excites many of us.
There are some beautifully designed IoT applications
Babolat has tennis rackets with sensors to track and analyze ball speed, spin, and impact location helping coaches and players improve their game. And what about the car that fixes itself. Where has that been all our life? When a Tesla vehicle needs repairs it can autonomously call for a corrective software download, or, if necessary, send a notification to the customer with an invitation for a valet to pick up the car and deliver it to a Tesla facility.
Then there are the really tough problems that we see being addressed with IoT, like in big industry. Companies like Joy Global are implementing smart, connected mining machines such as their longwall shearer to autonomously coordinate with other equipment to improve mining efficiency. Let’s not forget about the lifesaving applications like Medtronic’s implanted digital blood glucose meter that connects wirelessly to a monitoring and display device and can alert patients to trends in glucose levels requiring attention. It’s not hard to imagine a similar application for a pacemaker, allowing it to connect over wireless technology to communicate information like health, power, device performance and patient vitals. You can imagine how this scenario is helpful to exposing so much meaningful data to patients and physicians. This is the side of the Internet of Things that’s very compelling.
There’s no doubt all these use cases and applications will, and are attracting lots of attention.
There are some real opportunities for taking on the beastly and complex side of IoT
Now think about having to keep your pulse (pun intended) on 10,000 connected pacemakers, or kiosks, or self-service devices? How do you manage the full collection of these devices, some more complex than others, from an inventory, service, alert and notification perspective? How do you distribute software updates to that full collection of devices? How do you mine collected data in a way that provides an operator of large networks of devices with information to address and proactively manage and monitor hardware and software integrity issues that need to be remediated to prevent operating loss? How do you take all of the collected data received from these devices, and distill it down to only the most meaningful and non-distracting data for an operator?
With mesh networks you can merge the power of a group of devices to share valuable resources across the network. It’s a team of devices operating as a whole, not individual devices operating in silos. By applying advanced machine learning algorithms against device “big data” trends, we understand real-time performance against forecasted results.
This is the less sexy, but so important for realizing the full spectrum of opportunities within IoT.
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