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Every edge device has a story to tell — here’s how AI can help you parse the data and read between the lines

Now, artificial intelligence can help agencies parse that data and read between the lines of each story to solve complex mission challenges in real time, right...

This is the 11th article in our series, The Power of Technology.

When it comes to artificial intelligence, there’s a lot of talk today — both good and bad — about generative AI. But a narrow AI approach at the edge has the potential to transform real-time data use by tapping into the troves of information gathered by devices when and where it’s generated.

“Think about health care environments, say a Department of Veterans Affairs hospital or a Bureau of Indian Affairs clinic, for example. The cost of the medical equipment is expensive, and the need for it to be up and running properly is vital for patient wellness,” said Adam Rosenberg, business development manager for Optra, powered by Lexmark.

“And here’s the thing, nearly all of that equipment already has sensing technology in it,” Rosenberg said. “But how are we connecting to that sensing technology, that vibrational monitoring, that temperature anomaly detection that’s in the equipment? What is being done with it?”

Not enough is his answer. We talked with Rosenberg and Tony Celeste, executive director and general manager for Ingram Micro Public Sector, for our The Power of Technology series to learn how to do much more with such data at the edge.

Taking advantage of data where it is

The health care use case is an obvious one, both Rosenberg and Celeste said. By collecting data from medical and other devices in health care settings continually and then applying AI and machine learning to it, agencies can proactively monitor not just patient health but also the devices themselves.

Think about all the data-generating activities in a large hospital system — from dispensing medication and monitoring blood pressure to scheduling X-rays and processing lab orders — and all the physical equipment involved, Celeste said.

“From an edge AI perspective, imagine being able to provide a roadmap of where every device is and then being able to get to a specific device quickly,” he said.

Rosenberg took it a step further: “If we had proactive alerting that there was an anomaly on a piece of equipment that’s running abnormally and we need to send a technician out there today — rather than wait until the equipment breaks down — that is a game changer for health care. You can ensure patient wellness, ensure efficiency within that health care environment, and reduce costs ultimately.”

Now, broaden that out to other potential use cases, he said. Perhaps the Transportation Department could reduce traffic fatalities by monitoring road hazards, or a Defense Department agency could improve inventory control or manage predictive maintenance for a fleet of vehicles.

“This can affect every area in public sector,” he said.

Unleashing untapped potential of data at the edge

“We haven’t really realized the true benefit of it yet,” Celeste added.

Agencies are interested now because the data is available, computational power and network technology make real-time edge analytics feasible, and people see it as a way both to make better decisions and to reduce costs, he said.

“Networks have the available bandwidth to do things we weren’t able to do before, Celeste said. “And at the edge, the devices are more powerful themselves.”

There’s also the ability to automate at scale using AI across edge locations and by taking advantage of data housed in legacy IT systems, he said.

“AI at the edge potentially will give an agency the ability to collect and provide insights to address a mission challenge and then have the intelligence to go out and replicate that appropriately across legacy IT systems,” Celeste said. “That will let the agency enhance its mission and also bring new systems online more quickly.”

An obvious solutions pivot for Lexmark

Rosenberg said Lexmark created its Optra solution as a way to take advantage of multiple AI skills at the edge and manage them in a single dashboard across multiple, even thousands, of locations.

Its engineers turned the company’s years of experience managing printers and managed print services on its head and devised an edge AI platform, he said.

“We know about predictive maintenance. We have 7 million devices distributed globally — edge devices — they’re in the form of print. And 1.2 million of those are connected through our Managed Print Services, which offers predictive maintenance on our equipment,” Rosenberg said.

“Is there an issue with velocity feed to a printer? Is there a color calibration issue? MPS feeds that back to us so that we can ensure our customers are satisfied and confident in our devices and support. So that’s why it was such a natural evolution for us to move into the world of Edge and AI  because we were doing it for 20 years before there was an Internet of Things, before AI and edge were really the buzzwords that they are today.”

A critical element in developing Optra was security, he said. Lexmark’s MPS services provided the template there as well.

“What is compliant within an organization’s ecosystem? Where do they need this information shared to make sure that it’s secure, it’s private and it’s staying within compliance of that organization?” Rosenberg said. “All of that is able to be harnessed through the Optra portal and through each different artificial intelligence skill.”

To read more articles in The Power of Technology series, click here.

Learn more about Lexmark’s offerings through Ingram Micro Public Sector on Xvantage.

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