- Prepare Your Hardware and Simulink Model: Connect the board and create a Simulink model for the classifier created.
- Configure Your Model for Arduino Hardware: In your Simulink model, go to the ‘Modeling’ tab and click ‘Model Settings’ to open the ‘Configuration Parameters’ dialog box. In the ‘Hardware Implementation’ pane, set the ‘Hardware board’ parameter to your specific Arduino board, such as the Arduino Nano 33.
- Deploy Your Model: On the ‘Hardware’ tab in Simulink, in the ‘Mode’ section, select ‘Run on board’. Click ‘Build, Deploy & Start’ to compile and upload your model to the Arduino hardware.
- https://www.mathworks.com/help/simulink/supportpkg/arduino_ref/deploy-arduino-functions-to-arduino-hardware-using-matlab-function-block.html
- https://www.mathworks.com/help/simulink/supportpkg/arduino_ug/run-model-on-arduino-hardware.html
- https://www.mathworks.com/help/simulink/supportpkg/arduino_ref/getting-started-with-arduino-hardware.html
- https://www.mathworks.com/help/simulink/supportpkg/arduino_ref/identify-shapes-using-machine-learning-algorithm-on-arduino.html
- https://www.mathworks.com/help/simulink/supportpkg/arduino_ref/identify-punch-flex-using-machine-learning-algorithm-on-arduino-hardware.html