Tag: Data Science

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4IR IRL: The Impending Impact of the 4th Industrial Revolution

At Ericsson’s new D-Fifteen innovation and co-creation center in Silicon Valley, panelists for the #4IR IRL discussion provided an inside look at the strategies and use cases driving innovation. #IoT #IIoT

Moderated by WIRED’s Editor-in-Chief, Nick Thompson, this lively debate across multiple technology disciplines was arguably the best panel I’ve ever served on. There was never a dull moment for the audience as we painted a picture of what the 4th Industrial Revolution will look like.

Watch the video below:

Panelists:

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Internet of Things Predictions for 2017

Hyperspace

When it comes to #IoT predictions, 2017 will see solutions solving business pain points jump to hyperspace as VC funding dries up for many platform plays.

As we move into 2017, the marketplace will start to separate the “build it and they will come” crowd from IoT solutions that add compelling business value. When it comes to value creation, I anticipate we’ll finally see technologies that abstract machine learning algorithms plus data prep and cleansing to solve business problems for specific equipment. Think of this as an advanced analytics extension to existing digital twins. Vendors that seize upon this technology will see success in the $900M Industrial IoT market. On the other hand, the vendors promoting generic, often cloud-only platforms that try to be all things to all people will face a tough road ahead.

The IoT platforms set to take off are the ones tailored to specific industries and flexible enough to run on-premises, in hybrid mode and in the cloud as needed by customers. I’m not just talking about cloud offerings that work with edge gateways in the fog. I’m talking about solutions that are truly portable. On the security front, industrial customers will struggle to safely IoT-enable machines that aren’t securable and were never intended to be on the Internet. This will continue to be a problem until next generation versions of industrial equipment rolls off the assembly line with built-in compute, storage, IP networking and security. Expect lots of the industrial world to remain air-gapped and firmly in its M2M comfort zone.

Lastly, enterprises that can merge domain expertise, data science and machine learning will realize cost savings by stretching equipment maintenance cycles and avoiding downtime by predicting asset health. This represents the true value of IoT in business.