This project is designed to collect accelerometer data from a mobile device using an application, which is then sent to a computer for action prediction based on predefined actions.
The application used for data collection can be found at CollectAccelerometerDatav2.
The application has the following capabilities:
- Recognition of Different Actions: It can recognize various actions such as running, jogging, standing, cycling, etc.
- Segmentation of Actions in a Routine: The collected data can be segmented to identify different actions within a routine.
The project aims to implement the following features in the future:
- Improved Speed and Accuracy of the Model: Enhancements will be made to optimize the speed and accuracy of the action prediction model.
- Mobile Device Compatibility: The goal is to enable the entire process to run seamlessly on a mobile device.
To add a new action to the application, follow these steps:
-
Record Data: Execute
/recordData.py
to record data from your mobile device. Connect the device and wait for approximately 30 seconds to collect accelerometer data. The recorded data will be saved inyyyymmddhhmmss.csv
. -
Clean and Refine Data: Run
/processData.py
to clean and refine the collected data. You can also label the data at this stage. -
Train the Model: Execute
/model.py
to train the model using the cleaned and labeled data.
Once the model is trained, you can:
- Run the Application: Execute
./main.py
to start the application. Connect your device and enjoy the action prediction capabilities!