FogHorn Adds $30 Million in Series B Funding for IIoT Innovation

FogHorn Systems  has received a Series B round of funding totaling $30 million to support innovation in the Industrial IoT (IIoT) edge computing market segment. This new round brings FogHorn's total funding to $47.5 million and will be used to significantly expand the company's engineering resources and global go-to-market presence.

Intel Capital and Saudi Aramco Energy Ventures led the round, with new investor Honeywell Ventures and all previous investors participating, including Series A investors March Capital Partners, GE, Dell Technologies Capital, Robert Bosch Venture Capital, Yokogawa Electric Corporation, Darling Ventures and seed investor The Hive.

With more than 20 billion IoT-connected devices expected by 2020, according to Gartner's latest projections, FogHorn investor GE estimates that the industrial internet market segment will grow to $225 billion in that timeframe. The challenge, FogHorn contends is: How to generate actionable insights from all the real-time streaming data constantly being emitted by the profusion of physical, video/audio and other edge sensors deployed in any industrial environment—whether in manufacturing, energy, resources, transportation, smart cities or smart buildingswithout the transport and hosting costs, cybersecurity risk and operational latency associated with sending operations technology data across a network to a public/private cloud or remote data center.

FogHorn recently introduced the Lightning ML machine learning solution. Built on top of FogHorn's CEP (complex event processing)-driven edge analytics software launched in 2016, Lightning ML gives industrial customers the ability to train and execute machine learning algorithms and other data science models on streaming sensor data right at the source of the data. This facilitates the creation and enhancement of "digital twins" and other machine learning and AI models without the need to send all the sensor data to a cloud or data center for processing.

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