Welcome to the Fjord5G GitHub repository!
The Fjord5G is a 5G dataset for coastal maritime connectivity research. We conduct an extensive measurement campaign aboard research and public ferries in the Kiel Fjord, Germany, collecting GPS-located cellular data along maritime routes. These measurements cover the network conditions encountered in coastal and near-shore regions and provide insights into metrics such as signal strength, modulation, and bandwidth. The resulting dataset includes cellular measurements at a sampling rate of 1 Hz from two mobile network operators, four 5G routers, and two ferries for up to 12 months per router.
The paper is accepted at the 2025 IEEE 101st Vehicular Technology Conference: VTC2025-Spring. The dataset is available at Zenodo.
This project is licensed under the terms of the Creative Commons Attribution 4.0 International License.
- Clone this Git repository to your local machine using the following command:
git clone https://github.com/ds-kiel/Fjord5G.git
- Create a virtual Python environment (e.g. using pyenv)
curl https://pyenv.run | bash
pyenv install 3.13
pyenv virtualenv 3.13 Fjord5G
- Install the necessary Python packages by running:
cd Fjord5G
pip install -r requirements.txt -U
-
Download the dataset from Zenodo into the data folder
-
Analyze the data with the supplied Jupyter Notebooks
B. Denizer et al., "Fjord5G: A Comprehensive 5G Dataset for Coastal Maritime Connectivity", 2025 IEEE 101st Vehicular Technology Conference (VTC2025-Spring), Oslo, Norway, 2025, pp. 1-5
@INPROCEEDINGS{Fjord5G,
author={Denizer, Birkan and Landsiedel, Olaf},
booktitle={2025 IEEE 101st Vehicular Technology Conference (VTC2025-Spring)},
title={Fjord5G: A Comprehensive 5G Dataset for Coastal Maritime Connectivity},
year={2025},
volume={},
number={},
pages={1-5},
keywords={Dataset;coastal;maritime;LTE;5G;machine learning;QoS prediction;remote control;autonomous ferry},
}