This project is used for creating experimental environment for the simulation of the on-device federated learning process using the Flower framework. The project differentiates between training the model for two different data sets:

1. This example tracks activity for multiple users and the goal is to classify a given user activity. Dataset used is downloaded from UC Irivine's database - HARTH. The simulation of client data generation is performed by dividing the initial dataset
2. Second example's dataset is generated using the Arduino Nano 33 BLE Sense board and it tracks the activity of edge device:
   • collecting data (run script movement_model_dataset)
   • data formatting (run script create_csv)
   • in utils change number of classes and features to values 2 and 10 respectively
   • in first client and second one set values for labels on [0, 1]
   • in server's script number of clients is set to 2

Create virtual environment and install all needed modules:

pip3 install -r requirements.txt

Start the server

python3 server.py

Run all clients in different terminals (id in range 1 to 4)

python3 clientsubject<id>.py

For clients in second project follow the next steps

python3 clienteven.py

python3 clientodd.py

Teodora Kocic