White Paper: Edge Computing and Analytics

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edge computing

The need for speed has opened new frontiers in edge computing, especially for industrial IoT applications.

Written By

RTInsights Team

Nov 25, 2015

In some industrial IoT applications (IIoT), data can lose its value if it’s not processed quickly enough. In the power sector, for instance, constant power production or redirection is needed when aggregated equipment such as solar panels and lithium-ion batteries are located in remote areas.

This white paper from Hurwitz & Associates explores how edge computing moves analytics into the devices themselves, controllers, gateways, and in nearby data-aggregation centers. Here’s what you’ll learn:

Key challenges for IoT applications using real-time data, including cost, fragmentation, and latency;
Four key elements of an edge computing system, including data sources; edge analytics; data storage and analytics; and data insights–and the role played by each.
An edge computing architecture from Dell that helps to perform edge analytics at a mine with multiple power sources.

RTInsights Team

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The Value of Bringing Analytics to the Edge

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