FogHorn Systems, a software provider for the Industrial Internet of Things (IIoT), has announced the latest release of its edge-based software platform, Lightning. The new version is dubbed Lightning ML, as it’s bundled with several machine learning features, in addition to compatibility and ease-of-use updates.
Right off the bat, Lightning ML boasts an extremely small software footprint—the Micro edition of the platform comes in at under 256 MB, while the Standard edition (which encompasses Micro, but adds a few extra capabilities) is still a respectable sub-2 GB. This allows the platform to run on programmable logic controllers (PLCs), Raspberry Pis, IIoT gateways and other lightweight computers. Furthermore, Lightning ML is systemsagnostic and supports 32-bit ARM Cortex-A processors.
Since Lightning ML is made for the IIoTedge, all of its machine learning capabilities run locally—there is no waiting around for the cloud to send back results. Lightning ML’s so-called complex event processing (CEP) engine can utilize existing machine learning algorithms directly on industrial asset data in real-time. But if you still want to process in the cloud, Lightning ML can connect to any public or private cloud you want.
Another big selling point, according to FogHorn, is the user-friendly interface of Lightning ML. The platform has a simple drag-and-drop tool, which is designed for even nontechnical users to obtain actionable machine learning insights. “OT staffs are domain experts in their respective industrial environments, but not necessarily experts in edge computing and advanced IT. By giving them intuitive tools to automate, monitor and take action on their industrial data in realtime, operators can enhance situational awareness, prevent process failures and identify new efficiencies that lead to huge business benefits,” said FogHorn CTO Sastry Malladi.
The Lightning ML release attempts to optimize several factors that combine to enable the maximum impact of an IIoT solution. The small footprint, versatility, user-friendliness, edge capabilities and machine learning features are each important for IIoT end users, and together, they make a persuasive case for Lightning ML.
“FogHorn is accelerating the pace of innovation in edge computing by not just democratizing analytics but by making machine learning accessible to industrial operators,” said FogHorn CEO David C. King. “With the introduction of Lightning ML, we now offer customers the game-changing combination of real-time streaming analytics and advanced machine learning capabilities powered by our high-performance CEP engine.”
To learn more about FogHorn Systems’ role in IIoT, read Yokogawa to Collaborate on Industrial Internet of Things Architecture.