It always doesn’t make sense to accommodate all the intelligence for the systems in data centers, as the Internet of Things starts generating data from far-flung sensors and automating remote equipment.

The alternative found for this is edge computing, where smaller systems placed on the site in factories or other facilities will make a good judgment of IoT data and act on it. There seems to be a chance that the components of edge computing like gateways can shorten response time or just filter out sensor readings which don’t matter so they won’t add burden to the network.

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Building edge computing systems and writing their software like else in IoT is a still in progress. Limitation on the things like power and size are unique to this new field.

FogHorn Systems launched the Lightning software platform, designed to get real-time analytics and machine learning down to edge devices, which includes IoT gateways and even very low-powered processing components built into industrial products. Lightning is used as in proof-of-concept implementations in things like wind turbines, like pumps, buses, and locomotives.

“The technology also includes analytics component of General Electric’s Predix industrial IoT platform arriving later this year,” said FogHorn CEO David King.


Industrial IoT allows companies to monitor anything in their communication and act on their defect. FogHorn says “it’s the only company that can bring cloud-like analytics down to not just IoT gateways but hard-wired controllers embedded deep in equipment like locomotives. Some of these controllers run on proprietary operating systems that are 50 years old”.

Few biggest names in IT are going behind edge computing either with software or hardware. Cisco system is challenging this area with “fog computing” portfolio and announced a partnership with IBM early this year. The association tends to bring some of IBM’s Watson analytics capability into its edge computing systems.


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