Spectrum sensing on Arduino with a Convolutional Neural Network

The paper can be found .

This project is split into two for the training with Python in the training folder and doing inference on the Arduino in the arduino folder.

Setup

MATLAB (optional)

To generate new data you need to use MATLAB 2022b or older. In 2023 they changed the API for generating Zigbee signals and this code is not migrated.

GPU/CUDA (optional)

Uncomment the required Tensorflow packages depending on your system in requirements.txt.

See the supported dependencies table for TensorFlow here https://www.tensorflow.org/install/source#gpu. Make sure you have compatible versions for Python, TensorFlow, C Compiler, cuDNN and CUDA.

Python

1. Create Python 3.10 virtual environment.
2. Dependencies:
   1. Install Python requirements with pip install -r requirements.txt. If you want to run the TensorFlow Lite model on your PC then it must be Linux because there are no wheels available for macOS and Windows. The library tflite-runtime is commented out in the requirements.txt for this reason. The full TensorFlow model still works.
   2. For plotting TensorFlow models you also need the graphviz library to be installed on your system, which can be done with brew install graphviz or sudo apt install graphviz.
   3. xxd command must exist on your system so models and testing images can be converted to hexdumps in C files for the Arduino.
3. The data for training should be put in training/data/csv.

Arduino

1. Install the Arduino IDE.
2. Follow their instructions on getting started with TensorFLow Lite Micro library. https://docs.arduino.cc/tutorials/nano-33-ble-sense/get-started-with-machine-learning/
3. There is a conflict with the kissfft library that I've copied into the project because the TF Lite Micro library has its own copy. Inside the Arduino libraries folder in your system delete Arduino_TensorFlowLite/src/tensorflow/lite/experimental and Arduino_TensorFlowLite/src/third_party/kissfft.
4. Open the spectrum-painting.ino file in the Arduino IDE.

Useful links

• Great tutorial series on how to do TinyML on the Arduino Nano BLE with TensorFlow Lite Micro https://www.youtube.com/watch?v=BzzqYNYOcWc.
• Visualize any type of ML model with https://netron.app.