Set up a Raspberry Pi 5

Prepare a Raspberry Pi 5 with Raspberry Pi OS

The Raspberry Pi 5 is a widely available Arm-based board with full support for both Edge Impulse and AWS IoT Greengrass. This section covers flashing Raspberry Pi OS, enabling SSH, installing dependencies, and preparing the component configuration.

What you need

Before you begin, ensure you have the following:

• A Raspberry Pi 5 board with a power supply (USB-C, 5 V and 5 A recommended)
• A microSD card, 16 GB minimum (32 GB recommended for comfortable headroom)
• A Computer with an SD card reader to flash the OS image
• A Network connection (Ethernet or Wi-Fi) for the Raspberry Pi 5
• (Optional) A USB camera for live inference; without a camera, the Edge Impulse Linux Runner uses a sample video file

Flash Raspberry Pi OS

Download and install the Raspberry Pi Imager on your computer.

Raspberry Pi Imager

Open the Imager and configure the following:

1. Select Raspberry Pi 5 as the device.
2. Select Raspberry Pi OS (64-bit) as the operating system. The 64-bit version is required for aarch64 compatibility with Edge Impulse models.
3. Select your microSD card as the storage target.
4. Select the gear icon (or Edit Settings) to open the advanced options. Configure the following settings:
   • Set hostname: Choose a recognizable name (for example, rpi5-edge).
   • Enable SSH: Select Use password authentication.
   • Set username and password: Create a username and password that you’ll remember. Raspberry Pi OS no longer includes default credentials.
   • Configure wireless LAN: Enter your Wi-Fi network name and password if you’re not using Ethernet.
5. Select Write and wait for the flashing process to complete.

Insert the microSD card into your Raspberry Pi 5 and power the Raspberry Pi on. Give it a minute or two to complete its first boot.

Find the IP address

You need the IP address of your Raspberry Pi 5 to connect over SSH. There are several ways to find the address:

• Check your router’s admin page for connected devices.
• If you set a hostname (for example, rpi5-edge), try ping rpi5-edge.local from your computer.
• If you have a monitor connected, open a terminal on the Raspberry Pi 5 and run hostname -I.

Note the IP address for the next step.

Connect over SSH

Open a terminal on your computer and connect to the Raspberry Pi 5 using the username and IP address that you configured:

    

        
        
ssh your-username@<your-rpi5-ip-address>

    

Install dependencies

Update the package list and install the build tools, Node.js, and GStreamer plugins that the Edge Impulse Linux Runner requires:

    

        
        
sudo apt update
sudo apt install -y curl unzip
sudo apt install -y gcc g++ make build-essential nodejs sox gstreamer1.0-tools gstreamer1.0-plugins-good gstreamer1.0-plugins-base gstreamer1.0-plugins-base-apps

    

Greengrass Nucleus Classic is Java-based, so you also need to install a JDK:

    

        
        
sudo apt install -y default-jdk

    

Install available security updates:

    

        
        
sudo apt upgrade -y

    

(Optional) Verify the camera

If you have a USB camera connected, confirm that the system detects it:

    

        
        
ls /dev/video*

    

The output is similar to:

    

        
        /dev/video0

        
    

If nothing appears, check that the camera is plugged in securely and try a different USB port.

Save the component configuration

The following JSON configurations set up the Edge Impulse Greengrass component for the Raspberry Pi 5. Choose the configuration that matches your setup and save it to a text file on your local machine. You’ll paste it into the Greengrass deployment configuration in a later step.

With a USB camera

This configuration uses gst_args to capture live video from /dev/video0 at 640 × 480 resolution. The --force-variant float32 flag selects the float32 model variant. --silent suppresses console output because the Edge Impulse Linux Runner runs as a background service:

    

        
        
{
   "Parameters": {
      "node_version": "20.18.2",
      "vips_version": "8.12.1",
      "device_name": "MyRPi5EdgeDevice",
      "launch": "runner",
      "sleep_time_sec": 10,
      "lock_filename": "/tmp/ei_lockfile_runner",
      "gst_args": "v4l2src:device=/dev/video0:!:video/x-raw,width=640,height=480:!:videoconvert:!:jpegenc",
      "eiparams": "--greengrass",
      "iotcore_backoff": "-1",
      "iotcore_qos": "1",
      "ei_bindir": "/usr/local/bin",
      "ei_sm_secret_id": "EI_API_KEY",
      "ei_sm_secret_name": "ei_api_key",
      "ei_poll_sleeptime_ms": 2500,
      "ei_local_model_file": "/home/ggc_user/data/currentModel.eim",
      "ei_shutdown_behavior": "__none__",
      "ei_ggc_user_groups": "video audio input users",
      "install_kvssink": "no",
      "publish_inference_base64_image": "no",
      "enable_cache_to_file": "no",
      "cache_file_directory": "__none__",
      "enable_threshold_limit": "no",
      "metrics_sleeptime_ms": 30000,
      "default_threshold": 65.0,
      "threshold_criteria": "ge",
      "enable_cache_to_s3": "no",
      "s3_bucket": "__none__"
   }
}

    

Without a camera

This configuration reads inference input from a local sample video file instead of a live camera feed. The ei_local_model_file field points to a pre-downloaded model. ei_shutdown_behavior is set to wait_on_restart so that the Edge Impulse Linux Runner pauses after the video ends and waits for a restart command:

    

        
        
{
   "Parameters": {
      "node_version": "20.18.2",
      "vips_version": "8.12.1",
      "device_name": "MyRPi5EdgeDevice",
      "launch": "runner",
      "sleep_time_sec": 10,
      "lock_filename": "/tmp/ei_lockfile_runner",
      "gst_args": "filesrc:location=/home/ggc_user/data/testSample.mp4:!:decodebin:!:videoconvert:!:videorate:!:video/x-raw,framerate=2200/1:!:jpegenc",
      "eiparams": "--greengrass",
      "iotcore_backoff": "-1",
      "iotcore_qos": "1",
      "ei_bindir": "/usr/local/bin",
      "ei_sm_secret_id": "EI_API_KEY",
      "ei_sm_secret_name": "ei_api_key",
      "ei_poll_sleeptime_ms": 2500,
      "ei_local_model_file": "/home/ggc_user/data/currentModel.eim",
      "ei_shutdown_behavior": "wait_on_restart",
      "ei_ggc_user_groups": "video audio input users system",
      "install_kvssink": "no",
      "publish_inference_base64_image": "no",
      "enable_cache_to_file": "no",
      "cache_file_directory": "__none__",
      "enable_threshold_limit": "no",
      "metrics_sleeptime_ms": 30000,
      "default_threshold": 50,
      "threshold_criteria": "ge",
      "enable_cache_to_s3": "no",
      "s3_bucket": "__none__"
   }
}

    

What you’ve accomplished and what’s next

You’ve set up your Raspberry Pi 5, installed its dependencies, and saved the component configuration for your selected input source.

Your Raspberry Pi 5 is ready. Next, you’ll set up the Edge Impulse project .