The Arduino Nano 33 BLE Sense is a tiny development board with a Cortex-M4 microcontroller, motion sensors, a microphone and BLE - and it's fully supported by Edge Impulse. You'll be able to sample raw data, build models, and deploy trained machine learning models directly from the studio. It's available for around 30 USD from Arduino and a wide range of distributors.

The Edge Impulse firmware for this development board is open source and hosted on GitHub: edgeimpulse/firmware-arduino-nano-33-ble-sense.

Installing dependencies

To set this device up in Edge Impulse, you will need to install the following software:

1. Node.js v12 or higher.
2. Arduino CLI.
   • Here's an instruction video for Windows.
   • The Arduino website has instructions for macOS and Linux.
3. The Edge Impulse CLI. Install by opening a command prompt or terminal and run:

npm install -g edge-impulse-cli

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Problems installing the CLI?

See the Installation and troubleshooting guide.

Connecting to Edge Impulse

With all the software in place it's time to connect the development board to Edge Impulse.

1. Connect the development board to your computer

Use a micro-USB cable to connect the development board to your computer. Then press RESET twice to launch into the bootloader. The on-board LED should start pulsating to indicate this.

2. Update the firmware

The development board does not come with the right firmware yet. To update the firmware:

1. Download the latest Edge Impulse firmware, and unzip the file.
2. Open the flash script for your operating system (flash_windows.bat, flash_mac.command or flash_linux.sh) to flash the firmware.
3. Wait until flashing is complete, and press the RESET button once to launch the new firmware.

3. Setting keys

From a command prompt or terminal, run:

$ edge-impulse-daemon

This will start a wizard which will ask you to log in, and choose an Edge Impulse project.

4. Verifying that the device is connected

That's all! Your device is now connected to Edge Impulse. To verify this, go to your Edge Impulse project, and click Devices. The device will be listed here.

Next steps: building a machine learning model

With everything set up you can now build your first machine learning model with these tutorials:

• Building a continuous motion recognition system.
• Recognizing sounds from audio.

Looking to connect different sensors? The Data forwarder lets you easily send data from any sensor into Edge Impulse.