LoRaWAN gateway performance and vehicle tracking data
Data files
Feb 04, 2025 version files 1.33 MB
-
LoRaWAN_Gateway_Performance_and_Vehicle_Tracking_Data.7z
1.33 MB
-
README.md
1.98 KB
Abstract
This dataset was collected during an experiment conducted during NC State’s Packapalooza festival in August 2024. It evaluates the performance of LoRaWAN gateways by analyzing received telemetry data from a moving vehicle (i.e., helikite). Key metrics include Received Signal Strength Indicator (RSSI), Signal-to-Noise Ratio (SNR), transmission timestamps, and geographic data. The dataset supports various research applications such as optimizing IoT networks, enhancing data reliability, and developing energy-efficient LoRaWAN solutions. The raw and processed data, along with SigMF metadata and Python scripts for post-processing, enable reproducible analyses and integration into other workflows.
README: LoRaWAN Gateway Performance and Vehicle Tracking Data
https://doi.org/10.5061/dryad.w0vt4b939
Description of the data and file structure
The dataset contains detailed measurements collected from the transmitter and gateways, categorized as follows:
- Transmitter Information:
- Sent timestamp (sent_timestamp)
- Vehicle's geographic location (longitude, latitude, altitude)
- Vehicle's orientation (pitch, yaw, roll)
- Vehicle's velocity (velocity_x, velocity_y, velocity_z)
- Spreading factor (tx_spreadingFactor)
- GPS data (number_of_satellites)
- Package number and ID
- Gateway Data:
- Received signal strength (rx_rssi)
- Signal to noise ratio (rx_snr)
- Reception timestamp (rx_time)
- The channel used for receiving the data (rx_channel)
- RF chain id used for receiving the signal (rx_rfChain)
- Gateway geographic location (rx_location_latitude, rx_location_longitude, rx_location_altitude)
- Gateway ID (rx_gatewayId)
- Timestamp of the gateway (rx_timeSinceGpsEpoch)
- Transmission Details:
- Transmission frequency (tx_frequency)
- Data rate and frame counter (tx_bandwidth)
- LoRaWAN Data Rate (dr)
Files and variables
File: LoRaWAN_Gateway_Performance_and_Vehicle_Tracking_Data.7z
Description: The dataset is organized into the following files and folders:
- CSV Files:
failed_tx_packages.csv: Logs of failed transmissions.gateway-dataRate-Table.csv: Summary of data rates grouped by gateway.
- SigMF Files:
LoRa_data.sigmf-data: Raw signal data including SNR and RSSI information formatted according to SigMF v1.2.2 standards.LoRa_meta.sigmf-meta: Metadata information formatted according to SigMF v1.2.2 standards.
- Scripts:
example_to_convert_sigmf_to_csv.py: Script to convert SigMF files into CSV format.example_to_sigmf.py: Example script demonstrating how to use the dataset.
Methods
The experiment utilized a LoRaWAN-enabled LoStik IoT transmitter connected to a LattePanda MiniPC to transmit telemetry data at 1.5-second intervals. The transmitted packets contained a combination of timestamps, unique package identifiers, and vehicle telemetry. The data was received by multiple RAK7289CV2-V1 LoRaWAN gateways deployed at different locations (LW1, LW2, LW3, LW4, LW5, CC2, CC3, and RE2), which recorded signal strength (RSSI), noise levels (SNR), and reception timestamps.
To set up and manage the LoRaWAN network, ChirpStack, an open-source LoRaWAN Network Server, was used. Uplink payloads were sent without requiring confirmation at the MAC layer using the command mac tx uncnf <portno> <data>. For each transmission, the Data Rate (DR) was incremented by one, starting from DR0 and progressing up to DR3, enabling an evaluation of the network's performance across varying Data Rates.
The received data was logged by the gateways, capturing additional details such as channel frequency, bandwidth, spreading factor, and the gateway's location. This comprehensive setup provides insights into both vehicle movement and network performance under varying conditions. Python scripts were employed for post-processing and analysis, with sample workflows included to facilitate reproducibility.