Right now am working one of the use case using AWS Greengrass.
https://aws.amazon.com/greengrass/faqs/
AWS Greengrass is a service that allows you to take a lot of
the capabilities provided by the AWS IoT service and run that at the edge
closer to your devices. AWS Greengrass ensures your IoT devices can respond
quickly to local events, use Lambda functions running on Greengrass Core to interact with local resources, operate with irregular
connections, stay updated with over the air updates, and minimize the cost of
transmitting IoT data to the cloud.
Deep Learning
challenges at the Edge
Resource-constrained devices
CPU, memory, storage, power
consumption.
Network connectivity
Latency, bandwidth,
availability.
On-device prediction may be
the only option.
Deployment
Updating code and models on a
fleet of devices is not easy.
Value of ML
inference at the Edge
·
Latency
·
Bandwidth
·
Availability
·
Privacy
https://aws.amazon.com/solutions/case-studies/iot/https://aws.amazon.com/greengrass/faqs/
No comments:
Post a Comment