The value of edge computing lies in data

Cloud adoption is rising dramatically as enterprises seek computing and storage resources that can scale up and down based on changing business needs. But even given the cost and agility advantages of cloud computing, there is growing interest in another deployment model — edge computing, where computing occurs at or near the data source. It can support new use cases, especially innovative artificial intelligence and machine learning applications that are critical to modern business success.

At the Future Compute conference hosted by MIT Technology Review, three industrial technology experts said the promise of this advantage lies in data. Specifically, whether it’s a factory, a self-driving car, or a smart building system, data needs to be collected, processed, and analyzed closest to where it is generated.

The ability to run AI models directly on edge data without moving workloads to the cloud reduces latency and cost. Most importantly, experts agree, it’s the key to unlocking real-time insights that can separate leaders from laggards.

Enterprises are beginning to realize the role edge computing can play in driving successful data-driven business transformation. Gartner estimates that while only 10% of enterprise data was created and processed outside the data center and cloud in 2018, that number will reach 75% by 2025.

George Small, chief technology officer of Moog Inc., a $3 billion motion control solutions company, said he is seeing significant progress in edge applications.

"This is a real use case. What we're seeing now is where the value is being created," he said. "It's actually improving productivity significantly."

Convergence of Edge and Cloud

As data-driven business develops, enterprises need to create an IT environment that includes edge computing and cloud computing. Data collected and analyzed at the edge can initiate real-time responses to troubleshoot industrial equipment, prevent machine shutdowns, or redirect autonomous vehicles from harm.

At the same time, equipment data from machines or vehicles can be sent to the cloud and aggregated with other data for deeper analysis, driving smarter decisions and future business strategies.

"Connectivity has reached a benchmark point that is powering the idea of ​​an intelligent edge," Small said. "Intelligence starts at the perception level at the edge, extends to the system's network systems, and ultimately reaches the cloud. We think of it as a continuum."

Applications where the edge comes into play

Small said Moog is experimenting with edge computing for a variety of applications. In agriculture, the company is applying edge capabilities and machine learning recognition to almond and apple cultivation, helping harvesting equipment autonomously navigate terrain and increase crop yields. On the construction side, Moog's edge and AI-based automation work focuses on material movement—for example, turning part of an excavator into a robotic platform for automation.

Small also said that ongoing labor and productivity challenges have prompted Moog to experiment with edge-based automation in agriculture.

“There are situations where you don’t have as much of a structured environment, or people need to interact with the actual workplace.” “That’s our introduction to the definition of edge. We’re starting from a self-driving car perspective. of.

Another potential use case combines edge computing, 3D printing and blockchain to coordinate the on-demand, on-site output of spare parts. Small said Moog customers in industries such as aerospace and defense could Spare parts for critical equipment are manufactured on-site, using blockchain as a means of verifying the supply and integrity of parts.

Manish Sharma, vice president and general manager of Honeywell Sustainable Building Technologies, said at Honeywell Building technology company, edge computing is a key part of transforming building operations to improve quality of life. Smart edge sensors monitor temperature, humidity and carbon dioxide levels, helping create a smart building system that automatically adjusts energy and lighting usage to reduce costs while Optimize carbon neutrality and maintain building comfort.

Connecting heating, cooling and air filtration systems to edge devices creates an intelligent network that facilitates data sharing and makes smarter decisions closer to where the impact is greatest decisions.

Sharma said: "You are building a system of systems and doing the right calculations, you need to have a common network that can share data in milliseconds and make decisions at the edge level".

Best Practices for Edge Deployments

Panelists outlined some best practices that can help enterprises determine the right options for edge deployment while avoiding some of the more common deployment challenges.

Move computing power to where the data lives. Determining whether edge or cloud is best for a specific workflow or use case can lead to analysis paralysis. The truth is, however, that these models are complementary, not competitive.

Akamai​ "The general rule of thumb is that it's much better to move computation to data than the other way around," said Robert Blumofe, executive vice president and chief technology officer. “By doing this, you avoid backhauling, which can hurt performance and be costly. ”

Consider an e-commerce application that coordinates operations such as searching a product catalog, making recommendations based on history, or tracking and updating orders.

“It makes sense to do compute where the data is stored in a cloud data warehouse or data lake,” Blumofe said. The edge, on the other hand, is suitable for performing computations on data in motion—for example, analyzing traffic to support security operations.

Conduct lots of experiments. Edge computing is still in its early stages, and most enterprises are at the beginning of the maturity curve, evaluating how and where models can have the greatest impact. However, capabilities are improving rapidly and businesses cannot afford to sit idly by.

“You really need to start pushing because value is going to be created,” Small said. "You have to look out there for new opportunities - you don't just think of them, you have to find them."

Don't ignore ROI. Moog's Small notes that edge-enabled automation can help businesses do more with less labor and free up people to do higher value-added work. But beyond those obvious first-order productivity gains, edge automation has other, more difficult-to-quantify benefits, including replicability, he said.

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