FogHorn Systems announced Monday availability of Lightning ML, the newest version of its Lightning edge intelligence software platform for the industrial Internet of Things (IIoT). Lightning ML is an IIoT software platform with integrated machine learning capabilities and universal compatibility across IIoT edge systems.
Lightning ML brings the power of machine learning at the edge by leveraging existing models and algorithms so that industrial customers can seamlessly plug in and execute proprietary algorithms and machine learning models on live data streams produced by their physical assets and industrial control systems. The solution makes machine learning OT-accessible, as non-technical personnel can use FogHorn’s tools to generate powerful machine learning insights without the need to constantly rely on in-house or third party data scientists.
Lightning ML enables complex machine learning models to run on highly-constrained compute devices such as PLCs, Raspberry Pi systems, tiny ruggedized IIoT gateways, as well as more powerful industrial PCs and servers. Even with the addition of advanced machine learning capabilities, the complete Micro edition of the Lightning ML platform requires less than 256MB of memory footprint.
Accenture predicts that IIoT can add $14.2 trillion to the global economy by 2030. However, industrial environments present a challenge to status quo methods for data collection and analysis.
“The money and time required to move massive amounts of machine data to the cloud for analysis, only to send the results back to the edge, often makes little sense,” said Mike Guilfoyle, Director of Research and Senior Analyst at ARC Advisory Group. “In many instances cloud computing won’t be practical, necessary, or desirable. The reality is that edge intelligence is critical to a successful overall analytics strategy.”
“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. “The addition of FogHorn Lightning ML is a monumental leap forward in delivering on the promise of actionable insights for our IIoT customers. In the initial launch of FogHorn’s Lightning platform, we successfully miniaturized the massive computing capabilities previously available only in the cloud. This allows customers to run powerful big data analytics directly on operations technology (OT) and IIoT devices right at the edge through our complex event processing (CEP) analytics engine. 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.”
The newest version of Lightning is also systems-agnostic and supports 32-bit implementations of ARM® Cortex®-A processors, which are one of the most widely used processor types for IIoT deployments. Combined with its software miniaturization and machine learning capabilities, the Lightning platform’s very small footprint and support for ARM Cortex-A processors now makes edge intelligence available to an exponentially higher number of edge compute devices from many different hardware vendors.
“Fog computing requires a variety of different compute performance levels, all of which can be enabled by the flexible, low-power ARM architecture,” said Rhonda Dirvin, director of IoT and embedded, Business Segments Group, ARM. “FogHorn Systems’ Lightning platform supports and validates ARM-based solutions in OpenFog applications, and will enable new efficiencies and applications in the industrial edge computing space.
The FogHorn Lightning ML software platform can run entirely on premise or connect to any private cloud or public cloud environment. This gives users maximum flexibility in selecting the best deployment model in terms of IT infrastructure, security policy and cost.
FogHorn Lightning ML has been designed to empower OT users through a simple drag-and-drop authoring tool that abstracts away the complexities of an underlying IIoT deployment, allowing operators to focus on translating their domain expertise into meaningful analytics and machine learning insights.
“OT staff are domain experts in their respective industrial environments, but not necessarily experts in edge computing and advanced IT,” said FogHorn CTO Sastry Malladi. “By giving them intuitive tools to automate, monitor and take action on their industrial data in real-time, operators can enhance situational awareness, prevent process failures and identify new efficiencies that lead to huge business benefits. This is a very different approach from other IT-centric solutions that fail to leverage the tribal knowledge of key OT experts.”
Earlier this year, FogHorn announced that it has entered into a partnership agreement with Yokogawa Electric Corporation to develop and promote the use of “fog computing” solutions for IIoT. Yokogawa is active in the industrial automation and control (IA), test and measurement, and aviation other businesses segments. The IA segment plays a vital role in a range of industries including oil, chemicals, natural gas, power, iron and steel, pulp and paper, pharmaceuticals and food.