Dataset Open Access
Pei Tian; Fengxu Yang; Xiaoyuan Ma; Carlo Alberto Boano; Xin Tian; Ye Liu; Jianming Wei
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To make it clear how to use the scripts, we provide a <em>Jupyter notebook -- </em><a href=\"https://zenodo.org/record/5512850/files/dataset.ipynb?download=1\">dataset.ipynb</a> for dataset visualization. Please check the <a href=\"https://nbviewer.jupyter.org/urls/zenodo.org/record/5512850/files/dataset.ipynb/%3Fdownload%3D1\">notebook viewer</a> for a preview.</p>\n\n<p><strong>List of files:</strong></p>\n\n<ol>\n\t<li><em>dataset_03052021_15092021.csv</em>\n\n\t<ul>\n\t\t<li>The dataset includes LoRa connectivity and link quality, as well as environmental information, collected from May 3 to September 15, 2021.</li>\n\t</ul>\n\t</li>\n\t<li><em>data_analysis.py</em>\n\t<ul>\n\t\t<li>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).</li>\n\t</ul>\n\t<em>metadata_processing.py</em>\n\n\t<ul>\n\t\t<li>The script for pre-processing metadata into CSV files.</li>\n\t</ul>\n\t</li>\n\t<li><em>dataset.ipynb </em>\n\t<ul>\n\t\t<li>Jupiter notebook with dataset visualization and metadata pre-processing examples.</li>\n\t</ul>\n\t</li>\n\t<li><em>dataset_metadata.zip</em>\n\t<ul>\n\t\t<li>Metadata of the dataset in TXT and JSON formats.</li>\n\t</ul>\n\t</li>\n\t<li><em>topology_map.png</em>\n\t<ul>\n\t\t<li>A map of node deployment for creating topology maps.</li>\n\t</ul>\n\t</li>\n</ol>", "language": "eng", "title": "Dataset: Environmental Impact on the Long-Term Connectivity and Link Quality of an Outdoor LoRa Network", "license": { "id": "CC-BY-4.0" }, "relations": { "version": [ { "count": 12, "index": 7, "parent": { "pid_type": "recid", "pid_value": "4736501" }, "is_last": false, "last_child": { "pid_type": "recid", "pid_value": "5594944" } } ] }, "version": "v1.0.7", "keywords": [ "LoRa", "ChirpBox", "Connectivity", "Link quality", "Internet of Things", "Physical layer settings", "SX1276", "Temperature", "Weather" ], "publication_date": "2021-09-17", "creators": [ { "affiliation": "Shanghai Advanced Research Institute, Chinese Academy of Sciences", "name": "Pei Tian" }, { "affiliation": "Shanghai Advanced Research Institute, Chinese Academy of Sciences", "name": "Fengxu Yang" }, { "affiliation": "SKF Group", "name": "Xiaoyuan Ma" }, { "affiliation": "Graz University of Technology", "name": "Carlo Alberto Boano" }, { "affiliation": "Shanghai Advanced Research Institute, Chinese Academy of Sciences", "name": "Xin Tian" }, { "affiliation": "Nanjing Agricultural University", "name": "Ye Liu" }, { "affiliation": "Shanghai Advanced Research Institute, Chinese Academy of Sciences", "name": "Jianming Wei" } ], "access_right": "open", "resource_type": { "type": "dataset", "title": "Dataset" }, "related_identifiers": [ { "scheme": "doi", "identifier": "10.5281/zenodo.4736501", "relation": "isVersionOf" } ] } }
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Data volume | 211.8 GB | 3.1 MB |
Unique views | 327 | 8 |
Unique downloads | 285 | 6 |