FogHorn Systems has raised $30m in its second round of funding to expand its engineering teams in California and Pune, India that are working on Industrial IoT (IIoT) edge computing.
FogHorn recently launched Lightning ML with machine learning at the network edge. This uses FogHorn’s pioneering CEP (complex event processing)-driven edge analytics software that was launched in 2016 to allow industrial customers to train and execute machine learning algorithms on streaming sensor data at the source of the data.
- See also: Moving IoT analytics to the network edge
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 Ventures, Dell Technologies Capital, Robert Bosch Venture Capital, Yokogawa Electric Corporation, Darling Ventures and seed investor The Hive.
This new round brings FogHorn’s total funding to $47.5 million. “This major round of funding by many of the world’s largest and most innovative technology and industrial companies will enable FogHorn to continue its drive for industry-first innovation in the IIoT market segment,” said David King, CEO of FogHorn. “We have seen unprecedented interest from customers and partners in a huge variety of industries for advanced condition monitoring, predictive maintenance, asset performance management and process optimisation solutions.”
“Both the promise and challenge of IIoT lie in the ability to convert sensor data to actionable insights that improve customers’ operating efficiency and generate new sources of business value,” said Jonathan Ballon, Vice President and General Manager of Intel’s IoT Group. “As we’ve watched FogHorn’s progress with both leading IIoT solutions providers and major industrial end customers, we believe their edge analytics and machine learning technology will be a critical factor in enabling those operating efficiencies and delivering that business value.”
“For the oil and gas industry, harnessing IIoT insights will produce significant operating savings and spur major process improvements,” said Cory Steffek, Managing Director North America of Saudi Aramco Energy Ventures (SAEV). “We believe innovators like FogHorn will lead the way in redefining IIoT edge computing to deliver real-time analytics and machine learning value across our entire business — upstream, midstream and downstream.”
With more than 20 billion IoT-connected devices expected by 2020, according to Gartner’s latest projections, GE estimates that the industrial internet market segment will grow to $225 billion in that timeframe. This will require solving the fundamental computing challenge of generating 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 buildings — without the transport and hosting costs, cybersecurity risk and operational latency associated with sending all that operations technology data across a network to a public/private cloud or remote data centre.
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