Dataset: Environmental Impact on the Long-Term Connectivity and Link Quality of an Outdoor LoRa Network

This repository contains the long-term connectivity and link quality dataset collected on ChirpBox over 4 months (May -- September 2021) in the city of Shanghai, China. 

Scripts:

In addition to the dataset itself, we provide evaluation scripts for data analysis and visualization, in order to facilitate data exploration and re-use. To make it clear how to use the scripts, we provide a Jupyter notebook -- dataset.ipynb for dataset visualization. Please check the notebook viewer for a preview.

List of files:

1. dataset_03052021_15092021.csv
   • The dataset includes LoRa connectivity and link quality, as well as environmental information, collected from May 3 to September 15, 2021.
2. data_analysis.py
   • The script for dataset analysis and visualization.
3. metadata_processing.py
   • The script for pre-processing metadata into CSV files.
4. dataset.ipynb 
   • Jupiter notebook with dataset visualization and metadata pre-processing examples.
5. dataset_metadata.zip
   • Metadata of the dataset in TXT and JSON formats.
6. topology_map.png
   • A map of node deployment for creating topology maps.

How to use dataset:

• Download all files in this repository 
• Unzip the dataset_metadata.zip to the dataset_metadata folder
• Run the Jupiter notebook -- dataset.ipynb and check the results

Dependencies:

• Python 3:
  • networkx
  • seaborn
  • plotly
• One can use pip to install the package dependencies:

  pip3 install networkx
  pip3 install seaborn
  pip3 install plotly
  pip3 install ipykernel
  pip3 install --upgrade nbformat
  pip3 install -U kaleido