SiLabs xG24 Dev Kit
Last updated
Last updated
The Silicon Labs xG24 Dev Kit (xG24-DK2601B) is a compact, feature-packed development platform built for the EFR32MG24 Cortex-M33 microcontroller. It provides the fastest path to develop and prototype wireless IoT products. This development platform supports up to +10 dBm output power and includes support for the 20-bit ADC as well as the xG24's AI/ML hardware accelerator. The platform also features a wide variety of sensors, a microphone, Bluetooth Low Energy and a battery holder - and it's fully supported by Edge Impulse! You'll be able to sample raw data as well as build and deploy trained machine learning models directly from the Edge Impulse Studio - and even stream your machine learning results over BLE to a phone.
The Edge Impulse firmware for this development board is open source and hosted on GitHub: edgeimpulse/firmware-silabs-xg24.
To set this device up with Edge Impulse, you will need to install the following software:
Simplicity Commander. A utility program we will use to flash firmware images onto the target.
The Edge Impulse CLI which will enable you to connect your xG24 Dev Kit directly to Edge Impulse Studio, so that you can collect raw data and trigger in-system inferences.
Problems installing the CLI?
See the Installation and troubleshooting guide.
Edge Impulse Studio can collect data directly from your xG24 Dev Kit and also help you trigger in-system inferences to debug your model, but in order to allow Edge Impulse Studio to interact with your xG24 Dev Kit you first need to flash it with our base firmware image.
Download the latest Edge Impulse firmware, and unzip the file. Once downloaded, unzip it to obtain the firmware-xg24.hex file, which we will be using in the following steps.
Use a micro-USB cable to connect the xG24 Dev Kit to your development computer (where you downloaded and installed Simplicity Commander).
You can use Simplicity Commander to flash your xG24 Dev Kit with our base firmware image. To do this, first select your board from the dropdown list on the top left corner:
Then go to the "Flash" section on the left sidebar, and select the base firmware image file you downloaded in the first step above (i.e., the file named firmware-xg24.hex). You can now press the Flash button to load the base firmware image onto the xG24 Dev Kit.
Keep Simplicity Commander Handy
Simplicity Commander will be needed to upload any other project built on Edge Impulse, but the base firmware image only has to be loaded once.
With all the software in place, it's time to connect the xG24 Dev Kit to Edge Impulse.
Use a micro-USB cable to connect the development board to your computer.
From a command prompt or terminal, run:
This will start a wizard which will ask you to log in, and choose an Edge Impulse project. If you want to switch projects run the command with --clean.
Alternatively, recent versions of Google Chrome and Microsoft Edge can collect data directly from your development board, without the need for the Edge Impulse CLI. See this blog post for more information.
That's all! Your device is now connected to Edge Impulse. To verify this, go to your Edge Impulse project, and click Devices on the left sidebar. The device will be listed there:
Our firmware is equipped with a simple BLE demo showing how to start/stop the inference over the BLE and acquire the results.
To use the demo, first install the EFR Connect BLE Mobile App on your mobile phone:
Make sure your board is flashed with a pre-built binary. Power on the board and run the EFR Connect BLE Mobile App
Scan your neighborhood for BLE devices
Look for the device named Edge Impulse and tap Connect
Scroll down to Unknown service with UUID DDA4D145-FC52-4705-BB93-DD1F295AA522 and select More Info
Select Write for characteristics with UUID 02AA6D7D-23B4-4C84-AF76-98A7699F7FE2
In the Hex field enter 01 and press Send. This will start inferencing, the device should start blinking with LEDs.
For another characteristic with UUID 61A885A4-41C3-60D0-9A53-6D652A70D29C enable Notify and observe the reported inference results.
To stop the inference, send 00 to the characteristics 02AA6D7D-23B4-4C84-AF76-98A7699F7FE2
With everything set up you can now build your first machine learning model with these tutorials:
Looking to connect different sensors? The Data forwarder lets you easily send data from any sensor into Edge Impulse.
