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.
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
Shifu’s approach to adding device discovery capabilities is to integrate Project Akri (https://github.com/project-akri/akri). Akri will serve as Shifu's device management plane, while Shifu will handle the control and data planes.
You can view the approach and proposal here:
https://docs.google.com/presentation/d/1IB2qr1dYOxNVGVOeMB1zwoO2g9HTnvlpx2aaAsijUXg/edit?usp=sharing
Shifu’s LwM2M support proposal
First video demo https://youtu.be/tRk5pqiVJVA?si=syFt8Hl3Izhul3WT
10/22
LwM2M integration done
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 to run 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.