Edge AI NVR running YOLO models on Pi, containerized Yawcam-AI + PiStream-Lite + EdgePulse

I containerized Yawcam-AI into edge-ready CPU & CUDA Docker images — making it plug-and-play for RTSP-based object detection/recording/automation on SBCs, edge servers, or home labs.

It integrates with:

- PiStream-Lite: Lightweight RTSP cam feeder for Raspberry Pi
- EdgePulse: Thermal + memory optimization layer for sustained AI inference
- Yawcam-AI: YOLO-powered NVR + detection + event automation

Together they form a DAQ → inference → recording → optimization stack that runs continuously on edge nodes.

▪️ Persistent storage (config, models, logs, recordings)
▪️ Model-swap capable (YOLOv4/v7 supported)
▪️ GPU build that auto-falls back to CPU
▪️ Tested on Pi3 / Pi4 / Pi5, Jetson offload next

Would love feedback from anyone working with edge inference, AI NVRs, robotics, Pi deployments, or smart surveillance.

Repos:

- Yawcam-AI containerized:
https://github.com/855princekumar/yawcam-ai-dockerized

- PiStream-Lite (RTSP streamer):
https://github.com/855princekumar/PiStream-Lite

- EdgePulse (edge thermal/memory governor):
https://github.com/855princekumar/edgepulse

Happy to answer questions — also looking for real-world test data on different Pi builds, Orange Pi, NUCs, Jetson, etc.