LoED: LoRaWAN Gateway Data from an Urban Environment

Nine LoRaWAN gateways collected raw payload and metadata in an urban setting. The dataset is structured as daily CSV files and includes a parser for generating statistics. It supports research into low-power wide-area network performance and edge computing.

Use Cases

• Analyzing signal propagation and packet delivery based on raw payload and gateway metadata.
• Modeling network traffic patterns using daily time-series data files.
• Evaluating LoRaWAN gateway performance and reliability in an urban environment.
• Developing edge computing algorithms that utilize real-world IoT network data.

Strengths

• Data originates from nine distinct gateways, providing multiple observation points.
• Includes a dedicated parser (Jupyter notebook and Python script) for generating statistics, aiding reproducibility.
• Collection campaign is documented with daily granularity in separate CSV files.

Limitations

• Key metadata such as exact row count, file size, specific column names, and precise collection dates are not provided in the available descriptions.
• The 'Last updated' field is consistently listed as unknown across sources, indicating potential freshness concerns.
• One source citation note ('under submission') suggests a possible conflict or ambiguity regarding the definitive publication status.

Provenance

Source

Laksh Bhatia, Michael Breza, Ramona Marfievici, Julie A. McCann, Imperial College London

Collection Method

Collected from nine LoRaWAN gateways deployed in an urban environment.

Geography

Urban environment (specific location detailed in README.md files).