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Architecting the Industrial Internet by Carla Romano, Robert Stackowiak, Shyam Nath

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Data reduction and analytics

IIoT sensors have the potential to generate a huge amount of raw data that possesses inherent value. Additional analysis is often required to gain important insights. However, it can be expensive and time-consuming to transmit such volumes of data over networks. The speed and volume of data can make some preprocessing necessary prior to transmission.

A variety of preprocessing techniques are typical. Data volume might be reduced through aggregation. Another method of data reduction is to perform sampling and then filter samples within the stream. Statistical and machine learning algorithms can be applied at the data source or edge so that only the analytic results are transmitted through the network. Moving these ...

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