[Computerworld] IoT pushes analytics ever closer to the edge
September 13, 2016 – By Stephen Lawson
As the internet of things starts to generate data from far-flung sensors and automate remote equipment, it doesn’t always make sense to house all the intelligence for these systems in data centers.
The alternative is edge computing, where smaller systems located on site in factories or other facilities can make sense of IoT data and act on it. Edge computing components like gateways can shorten response times or just filter out sensor readings that don’t matter so they won’t burden the network.
But how to build edge computing systems and write their software, like so much else in IoT, is still a work in progress. The constraints on things like size and power are unique to this new field.
On Tuesday, Silicon Valley startup FogHorn Systems introduced the Lightning software platform, which is designed to bring real-time analytics and machine learning down to edge devices, including IoT gateways and even very low-powered processing components built into industrial products. Lightning has been used in proof-of-concept implementations in things like pumps, wind turbines, buses and locomotives. The technology will also be part of an analytics component of General Electric’s Predix industrial IoT platform coming later this year, FogHorn CEO David King said.
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