Enterprise IIoT: Edge Processing and Deep Learning

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Enterprise IIoT: Edge Processing and Deep Learning

See how to bring the power of deep learning to the IIoT edge with this sample flow that uses TensorFlow, Apache MXNet, Snse-Hat, NiFi, MiniFi, and more!

· IoT Zone ·
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Sending Data to an advanced analytics platform like Zoomdata is child's play. I added that as a live stream via REST while I am sending the JSON to be converted to AVRO then ORC for storage and Hive queries.

As part of the ingest, we store the images and make a current image for display.

See here and here for more details.

And below we see an overview of a flow to ingest both Apache MXNet + SenseHat Data as well as multiple rows of TensorFlow data

Then, we split our TensorFlow JSON data into individual JSON records.

This is how to split an array of JSON that doesn't have a top element.


apache mxnet ,apache nifi ,deep learning ,edge computing ,iiot ,iot ,minifi ,tensorflow ,tutorial

Published at DZone with permission of Tim Spann , DZone MVB. See the original article here.

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