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The Edge Gateway functions as the "nervous system" for the InfiniEdge AI project. It is designed to seamlessly connect AI models with your IoT devices at the edge.

Stakeholders:

• Tom Qin 

• Kris He 

• saiyan68 

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Objectives

• This work stream aims to optimize the device discovery experience at the edge, enabling edge gateways to automatically discover IoT devices using various protocols (S7, OPC UA, HTTP, etc.) and deploy the necessary resources so AI can interact with them.

  • Support more protocols like ROS/ROS2 to better serve embodied intelligence

  • Support LwM2M protocol

Approach

The Shifu’s approach for Shifu to add in adding device discovery capability capabilities is to integrate project Project Akri (https://github.com/project-akri/akri). We'll use Akri will serve as Shifu's device management plane and , while Shifu as will handle the control and data planeplanes.

The You can view the approach and proposal can be viewed here:

• https://docs.google.com/presentation/d/1IB2qr1dYOxNVGVOeMB1zwoO2g9HTnvlpx2aaAsijUXg/edit?usp=sharing

Shifu’s LwM2M support proposal

• https://github.com/Edgenesis/shifu/pull/878

• https://github.com/Edgenesis/shifu/pull/879

Progress

• First video demo  https://youtu.be/tRk5pqiVJVA?si=syFt8Hl3Izhul3WT

• 10/22

  • LwM2M integration done

    • https://github.com/Edgenesis/shifu/pull/1002

    • https://github.com/Edgenesis/shifu/pull/1001

  • Start working on tests and documentation

  • Begin working with ROS2

• 10/29

  • https://github.com/pytorch/executorch/blob/main/examples/models/llama/README.md running LLM on device guide.

  • Working with Meta team Running quantized llama 3.2 model https://ai.meta.com/blog/meta-llama-quantized-lightweight-models/ on S23 cell phone and try Edge AI function calling inference on device. The AI power are mostly on CPU now.

  • Continue waiting on another quantized model which running AI inference on NPU.