10.5281/zenodo.5594944
https://zenodo.org/records/5594944
oai:zenodo.org:5594944
Pei Tian
Pei Tian
Shanghai Advanced Research Institute, Chinese Academy of Sciences
Fengxu Yang
Fengxu Yang
Shanghai Advanced Research Institute, Chinese Academy of Sciences
Xiaoyuan Ma
Xiaoyuan Ma
SKF Group
Carlo Alberto Boano
Carlo Alberto Boano
Graz University of Technology
Xin Tian
Xin Tian
Shanghai Advanced Research Institute, Chinese Academy of Sciences
Ye Liu
Ye Liu
Nanjing Agricultural University
Jianming Wei
Jianming Wei
Shanghai Advanced Research Institute, Chinese Academy of Sciences
Dataset: Environmental Impact on the Long-Term Connectivity and Link Quality of an Outdoor LoRa Network
Zenodo
2021
LoRa
ChirpBox
Connectivity
Link quality
Internet of Things
Physical layer settings
SX1276
Temperature
Weather
2021-09-17
eng
10.5281/zenodo.4736501
v2.0.1
Creative Commons Attribution 4.0 International
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.
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.
List of files:
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.
data_analysis.py
The script for dataset analysis and visualization. One can use the functions in this script to derive network-level statistics (e.g., in terms of average number of correctly-exchanged packets), link-level statistics (e.g., in terms of SNR, RSS, and PRR), and node-level statistics(e.g., in terms of number of neighbours and temperature evolution over time).
metadata_processing.py
The script for pre-processing metadata into CSV files. One can use the functions in this script to convert metadata for each measurement saved in TXT and JSON formats to CSV files that include attributes such as link quality, connectivity, and environmental information, an example of which is dataset_03052021_15092021.csv.
dataset.ipynb
The Jupiter notebook contains examples of visualization and metadata pre-processing of datasets with functions in data_analysis.py and metadata_processing.py.
topology_map.png
The node deployment map used to create topology figures. A usage example is Figure 1 shown in the notebook dataset.ipynb.
dataset_metadata.zip
The dataset metadata is stored in TXT and JSON formats. Among them, link quality, connectivity and on-board sensor data are stored in TXT files and weather information are stored in JOSN files.
README.md
The README.md explains all the files in this repository and gives some examples of how to use the provided scripts to analyze the dataset.