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Five Sensors Real-Time with Pulsar and Python on a Pi (FLiP-Py-Pi-BreakoutGarden)

FLiP-Pi-BreakoutGarden FLiP-Py The easy way to build Python streaming applications from the edge to cloud. Code :   https://github.com/tspannhw/FLiP-Pi-BreakoutGarden Gear / Hardware Raspberry Pi 3 Model B Rev 1.2, Bullseye Raspian, armv71 Pimoroni Breakout Garden Hat 1.12" Mono OLED Breakout 128x128 White/Black Screen BME680 Air Quality, Temperature, Pressure, Humidity Sensor LWM303D 6D0F Motion Sensor (X, Y, Z Axes) BH1745 Luminance and Color Sensor LTR-559 Light and Proximity Sensor 0.01 lux to 64,000 lux VL53L1X Time of Flight (TOF) Sensor Software / Libraries Python 3.9 Pulsar Python Client 2.10 (avro) pip3 install pulsar-client[avro] Python Breakout Garden Python PSUTIL  https://pypi.org/project/psutil/ Python LUMA OLED pip3 install --upgrade luma.oled Libraries sudo apt-get install python3 python3-pip python3-pil libjpeg-dev zlib1g-dev libfreetype6-dev liblcms2-dev libopenjp2-7 libtiff5 -y StreamOps bin/pulsar-admin topics create "persistent://public/default/pi-sensors

Harnessing the Data Lifecycle for Customer Experience Optimization: Streaming Classifications On Twitter Streams

Harnessing the Data Lifecycle for Customer Experience Optimization: Streaming Classifications For a deeper dive see this past webinar: available here. In the use case solved for this webinar, I am a Streaming Engineer at an airline, CloudAir.   I need to find, filter and clean Twitter streams then perform sentiment analysis. Score Models in the Stream to Act As the Streaming Engineer at CloudAIR I am responsible for ingesting data from thousands of sources, operationalizing machine learning models as part of our streams, running real-time ELT/ETL processes and building event processing systems running from devices, servers and edge nodes. For today’s use case, one of our ML engineers had given me a model that was deployed into one of our production Cloudera Machine Learning (CML) environments. I logged into Cloudera Data Platform (CDP), found the model, tested it, and then extracted the information I need to add this model to our streaming ingest flow f