The Center of the IoT Data Universe Is Actually at the Edge
WHY YOU SHOULD CARE
Because at 94,000 feet, you don’t want interruptions in transmission.
By Nikhil Chauhan
The author, Nikhil Chauhan, is the Director of Product Marketing for GE Digital.
OZY and Predix from GE — the cloud-based development platform built for industry — have partnered to bring you an inside look at the future of digital industries, where people, data and productivity meet.
Anyone who has checked a movie schedule or restaurant review with their smartphone knows the benefits of the cloud. But when it comes to much larger safety-critical devices that require real-time response — think airplane engines, lifesaving medical equipment, water pumps in a desert — the cloud on its own, well, just doesn’t cut it. Many industrial applications operate in harsh and remote conditions, which challenges their ability to connect and cost-effectively transmit large quantities of data as needed. What if instead of simply collecting information for transmission to the cloud, applications could also process, analyze and act upon it? Why not add real intelligence to machines at the edge of the network, in the plant or field, and in the cloud?
First, a bit of nerdy knowledge. Industrial applications cannot rely exclusively on centralized data storage and processing. When they need to take immediate action, they can’t be encumbered by transmission bottlenecks — like 10,000 feet of ocean separating offshore oil rigs from safety-critical undersea blowout preventers, or water injection pumps battling temperatures of 50 Celsius in the middle of the desert. Enter edge computing. The edge is the physical location of the mission-critical machines — those blowout preventers and pumps — often at the edges of a network. Edge computing allows for analysis and knowledge generation to occur locally on these machines (also known as edge devices) instead of at the central core of data centers. Think of edge computing as the front door to the data kingdom. And the key? A modern industrial Internet platform.
What makes edge computing so revolutionary is that it can be optimized to run locally — at the individual asset, fleet or plant level. So, yes, it’s about improving performance of isolated pumps and high-flying aircraft, but also that of medical equipment, drones and smart traffic lights. Applications on these machines can not only collect data locally and respond to changes in that data but also perform meaningful analysis on the spot. Edge computing reduces the amount of information traveling to the data center, eliminating bottlenecks and improving performance. And there’s an added layer of security: Computing can continue on the edge device when a network outage occurs or there are connectivity limitations.
Case in point: the locomotive, the ultimate symbol of the first industrial revolution. Today it’s a pulsing, data-centric example of 21st-century edge-to-cloud computing. GE Transportation’s Evolution Series Tier 4 Locomotive carries more than 200 sensors that collect gigabytes of information and processes over 1 billion instructions per second. On-board edge computing allows it to analyze data and apply algorithms to help the vehicle run smarter and more efficiently. Which translates into multibillion-dollar savings for customers. Even with incredibly intelligent locomotives, railroads still experience hundreds of thousands of unexpected operational delays each year, costing the industry billions. The latest generation of trains can use edge-plus-cloud computing to ensure smarter maintenance and longer uptime and create game-changing equipment.
It’s not just about smarter trains. Similar benefits cut across multiple industries. “The edge-to-cloud approach is rapidly gaining favor throughout the industrial sector,” according to Greg Gorbach, vice president of ARC Advisory Group. “It’s a way to deploy powerful analytics where they are needed” and as quickly as they are needed, with minimum bottlenecks.
The main question: Does edge computing open the door to the value of customer data in industrial applications, just as the smartphone opened the door to value of consumer data in mobile apps?”
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- Nikhil Chauhan, OZY AuthorContact Nikhil Chauhan