Fourth in the series of posts as I digest all of the information I gathered at Hewlett Packard Enterprise (HPE) Discover 2018 in Las Vegas. This post focuses on use cases. Yes, people, there are people some in manufacturing and some not who are using HPE IoT and Edge computing for fun and profit.

First off, a panel assembled by Tom Bradicich, VP and GM IoT and Edge and Ph.D. entitled Intelligence at the Edge.

Nathalie Elad of Comcast- We are an aggregator of data from homes sending this data from local server to cloud. He is working with HPE on virtualization. No, it doesn’t collect individual family usage to sell to others (yes, it came up). But the company does need data to know how to channel bandwidth. The challenge-“we double bits every 18 months and need to flex up and down during the day.” Interesting stat—there used to be 3.3 devices per house, now may be 20 or even 30.

Tim Thai, Tesla- OT—IT is still a challenge. “The Edge is dynamic, wherever business sets up shop.” Regarding IoT, there are “Things” in manufacturing-control and sensors. They incorporate sensors in testing of technology in cars. Not to mention “there are a ton of sensors in a car.”

Philip Rostle, Alfa Romeo Sauber F1 racing, discussed F1 race car as the edge. There are lots of channels coming off the car during a race. They measure performance versus predicted. You think you have connection problems, he described connection in race as “variable”. Every car has a GPS. They track all cars in the race trying to predict status of the other cars. They run scenarios, analytics, quickly at the edge during a race to help determine strategy. Took “moonshot” server power to the edge so that they get maximum performance within the rules of F1.

In a special breakfast session, we talked with the CTO of the Ryder Cup and European PGA Tour. Think you know golf? Ever wonder about some of the stats that the TV announcers can quote during an event? Well, the tour requires a lot of data. And to get that data, they need connectivity. Golf is also an entertainment event. There are 50,000 spectators at the Ryder Cup. They all expect WiFi to access real-time information about the tournament.

First the data. Every shot has a dozen parameters to capture for every golfer. These are logged on the course. To connect, they use Aruba wireless networking devices. There are 30 switches and 700 access points. They collect 20K data points for scoring; 140K data points for other shot information. “Data drives insights that leads to performance for golfers.” They can track each golfer and also track spectator traffic patterns. An untold story, they lay 18km of fiber cable each tournament; ready to go for Wednesday morning and tear down beginning Sunday evening.

Mike Orr, director of digital transformation at Murphy Oil, uses Edgeline on oil platforms. He noted that his biggest hurdle was working with IT mostly due to its legacy software systems. He made this technology economics point—when oil went from $140 to $20, company laid off many workers. The only way he could get his work done was with technology.

I’ve already discussed the Texmark Chemicals “Refinery of the Future” use case, but I learned a few additional points at this conference.

Intel supplied streaming video analytics—used for physical security/monitoring, open gate for railway access allowed humans and critters into the site, monitored for exception to alert operators.

Deloitte is developing an IoT practice. It assembled an ecosystem including NI, Allied, ThingWorx, OSIsoft, SparkCognition AI for pumps. It also developed the operator dashboards for the project.

All together there were 12 partners in the ecosystem that completed the project that included predictive maintenance for two critical pumps and the video surveillance system.

HPE coordinated the entire project.

The insurance company was impetus to do something to upgrade the technology. Texmark kicked off the project by renting a party bus and taking 15 employees to the HPE IoT lab in Houston. They saw a demo of a pump with FlowServe monitoring and analytics. Employees discussed and picked the initial project targets—two critical pumps in the process plus the “video as a sensor” for the railway access. Getting early employee involvement was the key factor for successful implementation.

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