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FogHorn Brings Machine Learning to the IIoT

New software platform targeted at manufacturing verticals embeds machine learning at the network edge to make it quick and easy for anyone to understand data.

Sarah Thomas

July 11, 2017

2 Min Read
FogHorn Brings Machine Learning to the IIoT

Software startup FogHorn Systems is bringing machine learning to the edge of the Industrial Internet of Things (IIoT) with the release Tuesday of its latest big data analytics platform, Lightning ML.

The general idea behind edge computing, and the entire "fog sector," is that it's time-consuming and expensive to move data to the cloud to analyze and then send back to the edge. For many -- but not all -- use cases, weeding through data for the valuable bits and analyzing it where it originates at the edge is more efficient and lets that company respond in near real time. (See Fog Computing: The Virtualization Angle.)

It also requires an analytics platform with a much smaller footprint. FogHorn Systems says it successfully miniaturized the massive computing capabilities available in the cloud in the previous version of its Lightning platform, released in 2016, allowing its customers to run analytics on IIoT devices right at the edge via its complex event process (CEP) analytics engine. Today's update to the platform adds machine learning capabilities to the CEP engine.

FogHorn says its machine learning works with its industrial customers' existing models and algorithms; is easy to access and understand for non-technical personnel; and can run on devices as small as tiny, ruggedized IIoT gateways. The entire software platform, which can run on-premises or connected to a public or private cloud, requires less than 256MB of memory footprint. Lighting ML supports ARM32 processors, in addition to the x86-based IIoT gateways operations technology systems that the first release supported.

For more on machine learning and artificial intelligence, visit the dedicated automation content page here on Light Reading.

FogHorn, which raised $3 million in Series A funding in May, counts big names like GE, Bosch, Dell/EMC and Yokogawa amongst its current customer roster. While it doesn't serve telecom service providers, it does shares their perspective customer base in the industrial space for industry verticals like manufacturing, oil and gas, utilities and smart buildings. All are interested in helping manufacturers as they step up their investments in IIoT and seek ways to store, analyze and understand the data the IoT devices bring with them. (See Smart Cities See Fog Rolling In.)

Accenture forecasts that IIoT will add $14.2 trillion to the global economy by 2030, making now a critical time for investment, and the MPI Group studies suggest that 89% of manufacturers will increase IoT investments in the next two years. (See The Future Is Foggy – HR Report.)

— Sarah Thomas, Circle me on Google+ Follow me on TwitterVisit my LinkedIn profile, Director, Women in Comms

About the Author(s)

Sarah Thomas

Director, Women in Comms

Sarah Thomas's love affair with communications began in 2003 when she bought her first cellphone, a pink RAZR, which she duly "bedazzled" with the help of superglue and her dad.

She joined the editorial staff at Light Reading in 2010 and has been covering mobile technologies ever since. Sarah got her start covering telecom in 2007 at Telephony, later Connected Planet, may it rest in peace. Her non-telecom work experience includes a brief foray into public relations at Fleishman-Hillard (her cussin' upset the clients) and a hodge-podge of internships, including spells at Ingram's (Kansas City's business magazine), American Spa magazine (where she was Chief Hot-Tub Correspondent), and the tweens' quiz bible, QuizFest, in NYC.

As Editorial Operations Director, a role she took on in January 2015, Sarah is responsible for the day-to-day management of the non-news content elements on Light Reading.

Sarah received her Bachelor's in Journalism from the University of Missouri-Columbia. She lives in Chicago with her 3DTV, her iPad and a drawer full of smartphone cords.

Away from the world of telecom journalism, Sarah likes to dabble in monster truck racing, becoming part of Team Bigfoot in 2009.

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