A hands-on deep dive on using Apache Kafka, Kafka Streams, Apache NiFi + Edge Flow Manager + MiniFi Agents with Apache MXNet, OpenVino, TensorFlow Lite, and other Deep Learning Libraries on the actual edge devices including Raspberry Pi with Movidius 2, Google Coral TPU and NVidia Jetson Nano. We run deep learning models on the edge devices and send images, capture real-time GPS and sensor data. With our low coding IoT applications providing easy edge routing, transformation, data acquisition and alerting before we decide what data to stream real-time to our data space. These edge applications classify images and sensor readings real-time at the edge and then send Deep Learning results to Kafka Streams and Apache NiFi for transformation, parsing, enrichment, querying, filtering and merging data to various Apache data stores including Apache Kudu and Apache HBase.

https://www.datainmotion.dev/2019/08/updating-machine-learning-models-at.html