Complications plague still ‘infant’ IIoT

Article By : David Benjamin

The key to advancing industrial IoT is for more machines, more companies and more people to interconnect, interoperate and share data.

A panel member speaking at the Mobile World Congress has boldly declared that the intelligent use of industrial IoT even today has the power to eliminate the uncertainty of whether a company’s “hundreds of millions of investment will pay off, that their one dollar will turn into three dollars.”

The “predictive insights” provided by data gathered from connected industrial devices, said Brad Keywell, founder and CEO of Uptake, pose a great opportunity for profit creation with unprecedented “productivity, reliability and safety,” but only if industries “understand” how to take advantage of the power of connected devices.

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__Figure 1:__ *Brad Keywell, founder and CEO of Uptake*

Anticipating Keywell’s declaration, Venkat Atluri, a senior partner at McKinsey & Co., moderator of two panels discussing the potential of industrial IoT, cited statistics that forecast $4 trillion in value that will derive from these technologies in the next 10 years—an amount equal to Japan’s annual gross domestic product (GDP).

But Atluri added that this number represents only about a quarter of all companies who could exploit industrial IoT. Business models capable of fulfilling Keywell’s prediction, said panellist Doug Brent, vice president for technology innovation at Trimble Technologies, are in their “very early stages of infancy.”

One key to advancing the use of IoT effectively for industrial efficiency is for more machines, more companies and more people to interconnect, interoperate and share data, a promise complicated by issues of inertia, security and human nature.

The sheer power of inertia was expressed by panelist Enrique Herrera, principal for connected services at OSIsoft, who said that “agility is the key” for companies to respond to and use the sort of “predictive insights” produced by a constant flow of data into the industrial process. “But agility is hard for industrial companies who are used to buying equipment and letting it run for 20 or 30 years.”

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__Figure 2:__ *Enrique Herrera, principal for connected services at OSIsoft*

Indeed, as Uptake’s Keywell boasted, data science has exponentially reduced the sort of intensive analysis that can take three to six months. “You can deploy data science models,” he said, “in three days.”

He went on, “Create an insight. Deliver it to a human being in an industrial setting who has to take action.”

In those two sentences, Keywell capsulised the three key steps to the effective use of industrial IoT as laid out by panellist Brent, of Trimble Technology. Brent’s three steps: 1) collect data from lots of sensors, 2) apply a lot of analytics to understand the data and 3) take action.

Step three involves, of course, the human factor, which troubled most of the panellists. One panellist, Herrera of OSIsoft, suggested that the ideal human interface with the industrial Internet of Things would be a “hybrid individual.”

More seriously, Herrera said industries might require a “culture change” that broadens the outlook of its technology workers. He cited relatively young workers, “millennials who are getting the data, but are not concerned with how it’s gathered and how it translates operationally.”

Indeed, the greatest worry among all the panellists was the issue of data security in an emerging era of universal data sharing, a realm both governed and sabotaged by humans—like Herrera’s careless millennials—intervening in the torrent of information.

Panellist Thomas Engel, manager of technology innovation for John Deere, a manufacturer focused largely on farm equipment, noted that all of the company’s new machines send information constantly back to the company’s analysts. The farmers using the tractors and other machines don’t object to this exchange, but they balk at John Deere collecting “economic data.”

The sort of information, which touches on the farmer’s land use, livestock and personal income, is “much more sensitive,” said Engel. “You own it. If you share it, that’s your decision. We don’t look into that.”

“We want our customers,” added Brent, “to own the decision of where their data is going.”

Protecting sensitive data, even in an era when everyone seems to know something about everybody, is certain to slow the proliferation of the Internet of Things in general. This is particularly true in the “closed world,” in Herrera’s words, of many industries that could right now be much more closely–and productively–interconnected.

“It’s still very, very legacy,” said Herrera.

And still very, very human, as Engel finally emphasised. The impact on people of successfully sharing machine data can be profound. “It’s a slow process that started 20 years ago” at John Deere, he said. “Now, all our machines are connected, increasing productivity and efficiency for farmers. Next come the analytics, which will make farming more sustainable in the face of climate change. This is a prerequisite if we’re going to feed the world’s population in the next 30 years.”

This article first appeared on EE Times U.S.

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