Archive for machine learning

Distributed Analytics Forecast: Partly Cloudy with a Chance of Fog

Distributed energy showcases the role of advanced analytics Distributed energy continues to be a major focus for many utilities around the globe. That was certainly the case last week in San Diego at the electric utility industry’s major tradeshow for transmission and distribution, DistribuTECH 2017. As it was last year, one of the major themes […]

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Ambyint CEO on Analytics for Critical Infrastructure

IIoT Viewpoints is always on the lookout for disruptive IIoT-enabled solutions that address longstanding problems. ARC interviewed Ambyint CEO Nav Dhunay, and got his take on how analytics and wireless communications facilitates predictive maintenance for some or the world’s most critical infrastructure…oil fields. IIoT Viewpoints:  What is it about machine learning that makes it particularly relevant […]

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IIoT Technology Trends to Watch for in 2017

The automation industry appears to be evolving at a faster rate right now than at any time in its history, with IIoT being one of the primary drivers of change. IIoT and Digital transformation, enabled in part by the increasing convergence of operational technology (OT) and information technology (IT), is key for all organizations today, […]

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Smart Sensors are “Tip of the Spear” for IIoT

Much has been written and blogged about by ARC Analyst (and guest bloggers) over the last few years regarding the tremendous operational and business value that IIoT-enabled solutions can bring about for companies across all industries, but especially in asset-intensive industries such as oil & gas – upstream, midstream and downstream. One important component vital […]

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Blurred Lines Between Predictive and Prescriptive Analytics

Industrial companies have been using a form of prescriptive analytics for quite some time, particularly for maintenance and field service. Though rarely ever explicitly referred to as “prescriptive,” historic performance analytics—descriptive and diagnostic—are just that when they are underpinned with a knowledge base (and often automation) that enables a company to apply rear-view mirror prescriptive […]

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