🛠 Deploy Real-Time AI Inference on the Smart Display Module
Objectives
This tutorial aims to configure the Raspberry Pi Smart Display Module for real-time artificial intelligence tasks. By leveraging the dedicated M.2 slot, we will install a compatible AI accelerator (such as the Hailo) to process 4K video streams directly on the module. The goal is to create an intelligent display system capable of detecting objects or faces on professional SDM monitors, while maintaining silent and continuous 24/7 operation. This setup is ideal for interactive commercial signage or flight information systems requiring local analysis without cloud dependency.
Required Hardware
- Raspberry Pi Compute Module 5 (CM5).
- Smart Display Module for Raspberry Pi (SDM format, sold separately).
- Professional SDM-compatible monitor (with SDM connector).
- M.2 AI Accelerator card (e.g., Hailo-8) compatible with CM5.
- Stable power supply for the SDM monitor.
- USB-C cable for initial configuration.
- USB drive or SD card with Raspberry Pi OS (64-bit) installed.
Steps
- Hardware Assembly: Insert the Raspberry Pi CM5 into the Smart Display Module. Ensure connectors are aligned. Securely attach the M.2 AI accelerator card to the dedicated slot. Screw the card in place to ensure electrical and thermal contact.
- System Installation: Insert the SD card or USB drive containing Raspberry Pi OS into the designated port (if available via adapter or USB). Connect the module to the SDM monitor and power on. The system should boot automatically.
- Update and Drivers: Open a terminal via SSH or connected keyboard. Run the following commands to update the system:
sudo apt update && sudo apt full-upgrade -y
Install specific drivers for your AI accelerator. For Hailo, download the official SDK:
wget https://download.hailo.ai/latest/hailort_sw_tools.deb
sudo dpkg -i hailort_sw_tools.deb
sudo apt install -f
- Display Configuration: Verify that the SDM monitor is recognized. If 4K output is not active, modify the configuration file:
sudo nano /boot/firmware/config.txt
Add lines to force 4K 60Hz output if necessary, then reboot:
hdmi_group=1
hdmi_mode=97
- Inference Test: Download an object detection example using the M.2 accelerator. Run the demo script to verify that the video stream is processed locally with no perceptible latency.
Verification
Run lspci to confirm the M.2 card is detected. Use hailortcli scan to check the accelerator status. Display the video stream on the SDM monitor: AI detections should appear as overlays with a response time under 100ms. Check the module temperature with vcgencmd measure_temp to ensure passive cooling is sufficient.
Going Further
Explore integration with Raspberry Pi 5-compatible Content Management Systems (CMS) to broadcast live AI alerts. You can also optimize models to reduce energy consumption, which is crucial for 24/7 fanless operation.
Other tutorials for this board
- Getting started with the Raspberry Pi Smart Display Module
- Using Smart Display Module GPIOs
- Connect the Smart Display Module to the network for digital signage
- Getting Started with the Raspberry Pi Smart Display Module
- Interfacing GPIO and sensors with the Smart Display Module
- Deploying an autonomous digital signage with M.2 storage
Code examples for this board
gpio-led-blink-python.pyPythondht22-sensor-monitor.pyPythonwifi-status-checker.pyPythonm2-ssd-mount-check.shBashhailo-inference-test.pyPythongpio-led-status-indicator.pyPython