This is a repository with source code for thesis "Human Activity Recognition (HAR) based on WiFi CSI data"
Using Wi-Fi Channel State Information (CSI) is a novel way of sensing and hu-man activity recognition (HAR). Such a system can be used in medical institutions for their patients monitoring without privacy violence, as it could be with a vision-based approach.
The main goal of this thesis was to explore current methods and systems whichuse Wi-Fi CSI, conduct experiments to analyze how different hardware configura-tions affect the data and possibility to detect human activity, collect the dataset andbuild the classification model for HAR task. 8 experiments were performed, the dataset in 3 different rooms was collected, and LSTM-based classification model was build and trained. We’ve shown the full pipeline of building Wi-Fi CSI based system.
The dataset can be downloaded by the following link.
Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.
- Andrew Zhuravchak - Ukrainian Catholic University(UCU) student
- Oleh Kapshii - supervisor
This project is licensed under the GNU License - see the LICENSE.md file for details
- This repository is a fork from the Atheros-CSI-Tool-UserSpace-APP which is based on Atheros-CSI-Tool.
- RF-pose for inspiration for doing this work
- Cypress Semiconductor company, ASR Ukraine team and especially Oleh Kapshii for support and help