AWS Greengrass
No 1 About
Greengrass
AWS Greengrass is software that lets you run local compute, messaging, data caching, sync, and ML inference capabilities for connected devices in a secure way. ML Inference is a feature of AWS Greengrass that makes it easy to perform machine learning inference locally on Greengrass Core devices using models that are built and trained in the cloud. To sign up for the preview of ML Inference, click here.
Greengrass ML Use Cases
Video Processing |
| With AWS Greengrass ML Inference, you can deploy and run ML models like facial recognition, object detection, and image density directly on the device. For example, a traffic camera could count bicycles, vehicles, and pedestrians passing through an intersection and detect when traffic signals need to be adjusted in order to optimize traffic flows and keep people safe. |
Retail and Hospitality |
| You can run facial recognition models on in-store cameras to locate VIP customers and give them white glove treatment, such as moving them to the front of checkout lines, greeting them by name at the door, and offering them special discounts. Cameras locate the customers and alert customer service staff without having to send massive amounts of video data to the cloud, which is often a problem in large stores with poor cloud connectivity. |
Security |
| You can then use AWS Greengrass ML Inference to run and deploy the behavioral models directly on devices to detect deviations from normal behavior that could indicate an attack. When abnormal behavior is detected, the device can send the required data to AWS for further processing and action such as pushing a security fix. |
