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EFM Series: Using MiNiFi Agents on Raspberry Pi 4 with Intel Movidius Neural Compute Stick 2, Apache NiFi and AI

EFM Series:   Using MiNiFi Agents on Raspberry Pi 4 with Intel Movidius Neural Compute Stick 2, Apache NiFi and AI The good news is Raspberry Pi 4 can run MiNiFi Java Agents, Intel Movidius Neural Compute Stick 2 and AI libraries.   You can now use this 4GB of RAM device to run IoT with AI on the edge. Flow From MiNiFi Agent Running OpenVino, SysLog Tail and Grabbing WebCam Images Configure The Execution of OpenVino Python Applications on RPI 4 Events Returning from Raspberry Pi 4 Models Used Download model using downloader. Github https://github.com/tspannhw/minifi-rpi4-ncc2 DATE=$(date +"%Y-%m-%d_%H%M") fswebcam -q -r 1280x720 --no-banner /opt/demo/images/$DATE.jpg python3 /opt/intel/openvino/build/test.py /opt/demo/images/$DATE.jpg Software Apache NiFi Apache NiFi - MiNiFi Agents TensorFlow OpenVino Python 3 FSWEBCAM OpenCV DNN PSUTIL Python Libraries pip3 install getmac pip3 install psutil pip3 install --u

Barcelona DataWorks Summit March 2019

I just returned from this awesome event.   Not even a rough plane trip can damper my spirits after seeing all the amazing things and all that we got to do this year.   It was nice to see familiar faces from attendees from 2017 and 2018 including my friends from Prague and Germany! Thanks to Andy LoPresto, George Vetticaden, Dinesh Chandrasekhar, Purnima, Nathan, Dan Chaffelson for great pictures, talks, support and being an amazing team for Data in Motionists. Meetup The meetup was great and in the same hall as some other amazing meetups at the same time. A great experience for those at Summit early (and open to all people for free). https://www.slideshare.net/bunkertor/the-edge-to-ai-deep-dive-barcelona-meetup-march-2019 https://www.meetup.com/futureofdata-barcelona/events/259345951/ Highlight :  Dan spinning up NiFi at scale in the audience on Google Cloud on K8 with ease! Highlight :  Andy’s crushing it MiNiFi and NiFi presentation! I think he h

Using Raspberry Pi 3B+ with Apache NiFi MiNiFi and Google Coral Accelerator and Pimoroni Inky Phat

Using Raspberry Pi 3B+ with Apache NiFi MiNiFi and Google Coral Accelerator and Pimoroni Inky Phat Architecture Introduction First we need to unbox our new goodies.   The Inky Phat is an awesome E-Ink display with low power usage that stays displayed after shutdown!  Next I added a new Google Coral Edge TPU ML Accelerator USB Coprocessor to a new Raspberry Pi 3B+.    This was so easy to integrate and get up and running. Let's unbox this beautiful device (but be careful when it runs it can get really hot and there is a warning in the instructions).   So I run this on top of an aluminum case and with a big fan on it. Pimoroni Inky Phat It is pretty easy to set this up and it provides a robust Python library to write to our E-Ink display.   You can see an example screen here. https://github.com/pimoroni/inky Pimoroni Inky pHAT ePaper eInk Display in Red Pimoroni Inky Phat (Red) https://shop.pimoroni.com/products/inky-phat https://github.com

Apache NiFi + Deep Speech

Deep Speech with Apache NiFi 1.8 Tools:  Python 3.6, PyAudio, TensorFlow, Deep Speech, Shell, Apache NiFi Why : Speech-to-Text Use Case:  Voice control and recognition. Series : Holiday Use Case: Turn on Holiday Lights and Music on command. Cool Factor:  Ever want to run a query on Live Ingested Voice Commands? Other Options:  https://community.hortonworks.com/articles/155519/voice-controlled-data-flows-with-google-aiy-voice.html We are using Python 3.6 to write some code around pyaudio, tensorflow and Deep Speech to capture audio, store it in a wave file and then process it with Deep Speech to extract some text. This example is running in OSX without a GPU on Tensorflow v1.11. The Mozilla Github repo for their Deep Speech implementation has nice getting started information that I used to integrate our flow with Apache NiFi. Installation as per  https://github.com/mozilla/DeepSpeech pip3 install deepspeech wget - O - https : //github.com/mozilla/DeepSpeech/releases/download/v0.3.0/dee