[Course Certification Task] final exam for Cloud Native Edge Computing Course about community

[EnableAsync]

Hello, Thank you for your public course. I have learned a lot about kubeedge from it. And I have implemented an AI model training in the cloud and distributed the trained model to the Raspberry Pi system through KubeEdge. I also created a demo for this system, which controls the on and off of an LED light through face recognition and reports the data to the cloud through MQTT. The specific architecture is shown in the figure.

And, the deployment architecture is shown in the following figure.

The system front-end mainly includes training task management, device management, file management, and service management, as shown in the following figure.

The backend URL is: https://github.com/EnableAsync/cecl-go
The frontend URL is: https://github.com/EnableAsync/cecl-frontend
And the demo written for Raspberry Pi is: https://github.com/EnableAsync/cecl-example

I am not sure if this can meet the requirements for the final assignment, so I will temporarily write the content here. Thank you for reading 😉.

[xingleigao]

kubeedge/examples#129

Hi, I have enhance led-raspberrypi demo. Add web conrtoler for it. And update readme.md.

[dongjiec]

HI,this is Kubeadge Architecture design:

[0LuckyLove0]

Hi，this is collecting metrics from edge

[RyanZhaoXB]

Hi，this is collecting metrics from edge

hello @0LuckyLove0 , could you please propose your deploy.yaml to https://github.com/kubeedge/examples ?