Industrial IoT keeps moving: Three hardware predictions for 2017

(c)iStock.com/Leslie Achtymichuk

As the Internet of Things (IoT) continues to develop at a rapid speed, it’s always interesting to take a moment to pause and reflect on the fact that we’ve yet to scratch the surface of its impact.

We’re leaving 2016 behind and with that comes the opportunity to gauge where this technological revolution will take us in the upcoming year. While my guess is that no one person can answer that question, here’s a look at the top three buzzworthy trends I think we’ll witness in 2017.  

Major shift to endpoint analytics

The IoT is a game of speed and efficiency. Enterprises are creating next generation products and they’re learning from the successes and failures they’ve experienced in the past:

“In 2017, we’re going to see the conversation of IoT shift to endpoint analytics for faster decision making and reduced costs.”

Gathering and analyzing data at the node level removes the need to shuffle data from the endpoint to the cloud for processing. This practice of local computing puts us in a position to make decisions at a much faster pace and begins to phase out the client-server based model we’ve seen prevalent today. It’s a transition that can yield some big wins for business leaders in the areas of cost savings on connectivity and storage fees, not to mention it also helps reduce the amount of data clogging up the cloud.

Increase in distributed computing and emergence

Once our devices are talking to each other, this sets the stage for the proliferation of machine or “active” learning to take place:

In 2017, distributed computing and emergence will become the IoT game changers.”

With all of this information being gathered and processed at the node level, we’re going to start talking more about our opportunities to maximize that valuable information by having our devices communicate with each other to perform predictive analysis. Operating on a peer-to-peer basis rather than the traditional gateway-to-cloud model allows us to optimize our workflows based on the collective insights gained from the millions of end points we have out in the field.

Think of what this means for industries (such as auto and construction) , which can benefit from machinery that performs based on the given circumstance. The ability to predict outcomes right at the endpoint and adjust behavior is going to drive transformative business value for a lot of enterprises.

Starting with the end in mind, not the technology

As companies continue to learn from past successes and failures in the IoT, they’re seeing the need to put a higher emphasis on starting with the end goal in mind and backing into the technologies that can deliver on that:

From a strategy viewpoint, IoT pioneers are going to begin looking into not only the technology available, but more so the business use-case.”

It’s easy to get lost in the weeds with what technology can do without first identifying the business goal and impact on the market. Just because something can be done, doesn’t mean it should be. Companies developing industrial IoT products have done a better job at understanding the needs of their clients, but many have continued to focus more on their technology rather than market demands. Starting at the end and working backwards to find the exact technologies needed to carry out your platform promise is key.

Whether we’re ready or not, one thing is certain: The IoT will stop for no one. I’m excited to see what type of contribution 2017 will make as we continue to innovate new technologies that transform our day-to-day lives, both at home and in the workspace.

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