FogHorn's Lightning Software Moves Real-Time Processing to Edge

Following beta product development with flagship customer GE, FogHorn Systems has made its edge-analytics platform generally available.
By Mary Catherine O'Connor
Sep 14, 2016

Silicon Valley software company FogHorn Systems develops real-time edge-intelligence products for industrial internet applications. In other words, its software processes and analyzes data collected from sensors deployed in industrial applications—such as for tracking diagnostic data on manufacturing equipment, or monitoring for leaks or pressure changes inside an oil pipeline. Performing these processes at the point of data collection, rather than doing so in cloud-based servers, has two main benefits, says FogHorn Systems' CTO, Sastry Malladi. This approach, often called fog computing, reduces the volume of data transmitted to the cloud—along with associated cloud-hosting costs—and can enable faster decision-making.

"You might have hundreds of sensors, and they might be measuring data every few seconds," Malladi says. "To send that data through the cloud [where it is analyzed] and then wait for the signal back at the edge can add hundreds of seconds." In highly time-sensitive scenarios, that might be too long for any automated corrective action to be taken. "So you want to do as much processing on the edge as possible."

Click on the above chart, provided by FogHorn Systems, to view a larger version.
To that end, FogHorn Systems yesterday announced the general availability of its Lightning software platform, which it has been developing throughout the past two years and deploying with a small group of beta customers, including General Electric (GE), which uses Lightning to power data-analytics functions as part of its Predix IoT platform. GE uses Predix for onsite sensor data processing in Industrial Internet of Things (IIoT) applications by running it, and Lightning, on edge devices, such as networking equipment and gateways.

"Predix did not have real-time data processing," Malladi explains, "and that is what we offer."

FogHorn Systems' Sastry Malladi
Specifically, GE is using Lightning at one of its plants that produces industrial-grade electrical products for power grids. Here, it is working with FogHorn to apply real-time analytics for maximizing manufacturing yields from data emitted by hundreds of sensors attached to each assembly line.

"By the end of the year, Predix will have our capabilities embedded inside it," says FogHorn Systems' CEO, David King, who adds that his company is also working with a handful of other customers that he cannot disclose.

Lightning's analytics engine processes streaming datasets from sensors and then forwards them on to an application that triggers an action or alert, or simply passes them onto another database, such as a data historian, which may be cloud-based. For example, King explains, Lightning is being used in combination with pressure, flow and temperature sensors at a manufacturing plant in order to monitor pumps and control valves. The software analyzes the sensor data to identify variances that could lead to damage to seals, bearings or impellers (rotating arms) inside the pumps and control valves. Lightning triggers alerts that are sent to maintenance workers, advising them to take corrective action (such as increasing or decreasing flow) in order to avoid a failure. Then, the software passes the data to a historian, which further analyzes the information for predictive maintenance applications.

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