aws-samples / use-influxdb-and-grafana-to-visualize-ml-output-with-awsiot-greengrass-v2 Goto Github PK

This repository compliments the blogpost How to use InfluxDB and Grafana to visualize your ML output at the edge with Greengrass v2.
https://aws.amazon.com/blogs/opensource/how-to-use-influxdb-and-grafana-to-visualize-ml-output-with-aws-iot-greengrass/

Machine learning (ML) algorithms are widely used for computer vision (CV) applications, such as imageclassification, object detection, and semantic segmentation. With the latest development of the IndustrialInternet of Things (IIoT), ML algorithms can be directly implemented at the edge device to process image dataand perform anomaly detection, such as for product quality assurance tasks at shop floors with low latency. Therecently released AWS IoT Greengrass version 2 (Greengrass v2) helps developers deploy CV ML applications atthe edge with the necessary customer data pipeline components, including data ingestion and datapreprocessing logics.In this blog post, we’ll show an end-to-end workflow for using open source tools with AWS IoT Greengrassversion 2 to visualize ML inference results in near real-time on an edge device.

This library is licensed under the MIT-0 License. See the LICENSE file.