AI on a Pi? Believe it!



AI Summary

  • Pineberry AI Hat Overview
    • Connects to Raspberry Pi 5 via PCIe express bus
    • Features M2 slot for Coral AI Edge TPU
    • 2,000 CPU
    • Interface supports gen 3 speeds for enhanced AI performance
  • Frigate NVR Home Surveillance Test
    • Raspberry Pi setup with Edge TPU and $15 webcam
    • Surveillance records upon motion detection
    • Achieved faster inference times than recommended hardware
  • Setup Process
    • Mount TPU onto AI hat with spacers and screws
    • Secure 16p FPC ribbon
    • Connect AI hat to 8 GB Raspberry Pi 5
    • Total setup cost: 19 for AI hat, $25 for Coral AI chip)
  • Performance and Configuration
    • PCIe version offers better thermal management than USB version
    • Raspberry Pi OS 64bit setup with micro SD card, Wi-Fi, and SSH
    • Script to install drivers and configure operating system
  • Testing the TPU
    • Verify TPU installation and expose to Docker
    • Use pyCoral library and Frigate for home surveillance NVR
    • Docker Debian 10 VM setup for running pyCoral
    • Install MQTT for messaging relay service
    • Configure Frigate with YAML file and IP address
  • Frigate Optimization and Usage
    • Add FFmpeg preset for Raspberry Pi 64bit h264 hardware acceleration
    • Set up web UI for camera management
    • Person detection records events when a person is in frame
  • Performance Insights
    • Smooth operation on Raspberry Pi 5
    • 7.49 millisecond inference time
  • Potential Enhancements and Alternatives
    • PCIe may offer lower latency than USB
    • Camera Module 3 with 12 MP sensor for HD IoT camera
    • Possibility of dual Edge TPU setup
    • Raspberry Pi may release an official M2 hat for NVMe storage
    • Single TPU can support around 10 cameras
  • Personal Recommendations
    • Consider USB accelerator to keep PCIe slot open for NVMe storage
    • Explore custom TensorFlow Lite models with pyCoral library

For more details, refer to the full blog post in the video description.