On the IT Innovation Insider, Jason Langone and Greg O’Connell of Nutanix say agencies must address security, governance and a host of other issues to successfully use data collected in the field in near-real time.

The internet of things or connected devices and artificial intelligence are quickly emerging in the federal sector.  These emerging—if we can even call them emerging anymore–technologies are impacting the federal market in a big way.

Over the last few years the use of connected devices has grown from sensors on networks to sensors in the field to measure agriculture output. It’s all about bringing computing to the edge.

At the same time, there are security concerns that come with it. The National Institute of Standards and Technology will be releasing an updated guidance to adopting IoT and addressing security concerns in the coming months.

Agencies have to understand how to harness these opportunities, address the challenges that come with them and, maybe most importantly, take advantage of the power of the technology evolution to bring services, compute power and data to the tactical edge.

Jason Langone, a senior director for IoT and AI at Nutanix, said the agencies are recognizing more and more that much of the data it uses is generated at the field where its employees are meeting their mission and the old approach of sending that information back to a centralized processing center isn’t working.

“The way developers have been developing applications have moved from legacy middleware apps to containerized applications that are much easier to move out to the edge. And everything is IP connected now and has the ability to send data now,” Langone said on the IT Innovation Insider. “We are collecting this data, what can we now do with it and how can we make smart correlations to take intelligent actions.”

Greg O’Connell, a director for Nutanix, said while devices have generated data at the edge for years, the difference is the underlying infrastructure, such as cloud services, can move or process that data quickly, letting users make decisions in near-real time.

O’Connell said research finds that devices and applications at the edge will generate 40 times more data by 2020 than what’s currently being generated.

“With all of this data comes the requirement to manage and process the data,” he said. “There is a broad range of examples that span organizations and agencies within government that are absolutely flat-footed yet need to adopt edge-based capabilities. To give you an example, there is an Air Force program office that is responsible for flight suits and helmets for pilots. We gather terabytes of information on military jets by the minute, yet to date, we gather zero physiological information on the pilots themselves. This is a classic example of IoT and edge computing where if we could better collect information with the sensors and process it in real time…we could take advantage of that to protect the pilots.”

Langone said agencies and developers must keep in mind the challenges of deploying apps to the edge, given in some cases there is low bandwidth or connectivity.  He also said an additional challenge is the number of devices that employees use in the field could number, in some cases, in the hundreds of thousands, which adds more complexity to the effort.

“There are a couple of things to think about. One is the sensor data, where does that live at the edge and how is that encrypted as well as the machine learning logic that is delivering the value?” Langone said. “If that edge device were to grow legs and walk away or to be stolen, how do we ensure that we’ve lost nothing?”

This is why Langone and O’Connell recommend agencies apply IoT devices and AI only after they know what problem they are trying to solve. The technologies and devices have to be a part of a larger business solution.

“One of the working relationships I’ve seen is when the chief data officers is fielding requirements from the business or mission. They typically understand they have a problem with something. And the CDO often responsible for developing that strategy and ultimately deploying the solution to solve that problem” Langone said. “When that is not a connection that is functioning in an agency, those things are in a void and it’s difficult to come up with something specific to solve.”

O’Connell said agencies need to address these challenges today because the growth of IoT, AI and machine learning will contribute trillions of dollars to the U.S. economy over the next 10 years and create tens of millions of new jobs.

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