WiFind is a project focused on indoor localization using WiFi Fingerprinting techniques. The main objective is to determine the position of a user inside a building by analyzing Wi-Fi signals (RSSI) from various Access Points (APs). This project was conducted in the Ercolani building of the University of Bologna, where real-world data was collected to create a customized dataset.
Instructions on setting up the project environment:
- Clone the repository
- Install dependencies:
pip install -r requirements.txt
The project uses Wi-Fi fingerprinting data collected in real-world conditions. The data is categorized as follows:
- Raw Data: Located in
/data/raw/, it includes unprocessed Wi-Fi signal scans collected in different rooms and conditions (Empty,Crowded). - Processed Data: Located in
/data/processed/, it includes datasets that have been preprocessed and transformed for analysis and modeling purposes.
- Navigate to the project directory:
cd /path/to/wi-find - Start Jupyter Notebook:
jupyter notebook
- Open and run: main.ipynb
/data: Contains raw and processed data./src: Source code for the project./scripts: Python scripts for data preprocessing and analysis./notebooks: Jupyter notebooks for experiments and visualization.
This project is licensed under the CC0 1.0 Universal license.