Recent Wikibon research has shown that a compute model that keeps as much data as possible at the edge can save enterprise customers more money than a process that ships data to the cloud (Wikibon is owned by the same company as SiliconANGLE). Industrial internet of things startup FogHorn Systems Inc. has set out to prove that finding right.

FogHorn provides intelligent software for edge computing in the industrial sector. Its customers include businesses in the transportation, manufacturing and petroleum fields, as well as smart cities and buildings.

“They use our software to predict conditions in real time or do condition monitoring or predictive maintenance … and successfully save a lot of money,” said Sastry Malladi (pictured), chief technology officer at FogHorn. “When there is a problem, they want to know before it’s too late.”

Malladi spoke with George Gilbert (@ggilbert41) and Lisa Martin (@LuccaZara), co-hosts of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, at the BigData SV event in San Jose, California. They discussed how FogHorn’s technology runs in highly compressed environments alongside evolving software solutions for edge data management. (* Disclosure below.)

Smart city elevators on a Raspberry Pi

FogHorn’s software processes sensor-driven data in less than 159 megabytes of memory, within a single core to a dual-core central processing unit, according to Malladi. There is almost literally no storage because FogHorn provides a real-time processing engine in an industrial framework.

“One of our largest smart city building customers … runs in a Raspberry Pi [small computer] on millions of elevators, with dozens of machine learning algorithms on top of that,” Malladi explained. “That’s the kind of size we’re talking about.”

The startup is focused on a difficult problem, the management of data in motion rather than data at rest. It’s an area drawing more attention as “internet of things” devices come online and companies roll out new technologies, such as the latest Hortonworks DataFlow framework, which is based on open-source NiagaraFiles registry software.

“A lot of these seemingly similar software capabilities that people talk about don’t quite exactly have either the streaming capability or complex event processing, or the real-time or the low footprint,” Malladi said. “What we have is a combination of all of that.”

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of the BigData SV event. (* Disclosure: FogHorn Systems Inc. sponsored this segment of theCUBE. Neither FogHorn Systems nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE