Money At The Edge: Channel Partners See The Benefits Of Pairing Edge Computing With IoT

As more customers adopt Internet of Things applications, solution providers say edge computing applications – where data is processed and analyzed at the end device level – are becoming more prevalent.

"More IoT devices and sensors need to be ubiquitous to their environment," said Aaron Kamphuis, IoT practice manager at Open Systems Technologies, a Grand Rapids, Mich.-based solution provider. "We're bundling in edge capabilities as part of our overall IoT solution so we can come in and figure out what data needs to be captured and how to capture it."

In edge computing, sensors and other connected devices collect and analyze the data locally, alleviating the dependence on cloud or internet connectivity in specific situations where information needs to be processed quickly, reliably and securely.

[Related: AWS Launches Greengrass Software, Giving Partners A Way To Boost Edge Computing In IoT Devices]

Customers are recognizing the business benefits of bringing that intelligence closer to the end customer, and they're spending accordingly. Market research firm IDC predicted that by 2019 at least 40 percent of IoT-created data will be stored, processed, analyzed and acted upon close to, or at, the edge of the network.

Open Systems Technologies recently used edge computing capabilities while working with Herman Miller to create a cloud architecture and data analytics platform that enables a cloud-connected furniture system.

This platform, which takes real-time information on sensor-enabled furniture, helps organizations better understand their employees' changing needs in the workplace so that they can control operational costs and improve space utilization. For the platform to work properly, the furniture needs to be constantly collecting data, even if the internet access is spotty.

For Herman Miller, OST used edge computing capabilities so that the platform could still run even if the internet connection was down, said Alex Jantz, IoT solutions architect at OST.

"We were able to leverage our edge computing as a mechanism for allowing a lot of furniture to connect to a gateway and have this interaction with users, while not being limited by the internet," he said. "So customers can still use their table and chairs, and not have the internet connection get in the way."

AWS and Microsoft have been building edge analytics services into their overall Internet of Things platforms.

Microsoft announced a new Azure IoT Edge service at Build, its recent developer conference, saying it will help enable developers to move their computing needs to Windows and Linux devices – and utilize Microsoft's array of services, including Azure Machine Learning, Stream Analytics, and the Azure IoT Hub.

AWS in 2016 introduced Greengrass, which builds off AWS IoT and AWS Lambda – a "serverless" compute service that enables users to run "stateless" code on servers, so that it isn't attached to any particular infrastructure and will always run when triggered.

AWS' service will allow developers to write Lambda code that can run straight from devices, and is built for offline operation so that IoT data can continue to be processed even when connectivity to the cloud is temporarily unavailable.

"Edge is becoming much more important than I had predicted it would be … there's a continued push from customers to get closer and closer to the edge," said Brian Blanchard, vice president of cloud solutions at 10th Magnitude, a Chicago-based solution provider. "The largest opportunities for the channel is adding data analytics to managed service providers' stack with a data driven approach."

Analytics at the edge has a particularly large role in manufacturing, where mission critical machines may need to process and analyze data in a split second, solution providers told CRN.

Manufacturing vendors focused on operational technology have built up their own strategies around edge technology. GE Digital's Predix software platform, for example, includes a range of integrated technologies at the edge, including Predix Machine for device provisioning, Predix Connectivity, and Predix EdgeManager for management, configuration, and administration of edge devices.

Predix performs two types of data analysis: operational analytics, which analyzes information in real time at the source – like a wind turbine or MRI machine – that detect split-second changes to prevent damage and optimize performance, and historical analytics, which collects and analyzes data over time.

"It is a trend for manufacturing vendors to create these tools at the edge," Jeff Miller, chief technologist of smart manufacturing at Avid Solutions, a Winston-Salem, N.C.-based systems integrator. "Customers are looking for analytics at the edge to help with their [operational technology] applications."