SharifLoc16 is a LoRa RSSI-based dataset collected in a sports hall for indoor localization research. It comprises 4471 rows and 16 columns of RSSI measurements, plus ground truth coordinates. The dataset was created by Melika Rajabi and is hosted on Harvard Dataverse.
Use Cases
- Train RSSI-based localization models based on the 4471 rows of signal measurements.
- Evaluate the accuracy of indoor positioning algorithms based on the provided ground truth coordinates.
- Analyze signal propagation patterns in a sports hall environment based on the inter-gateway link measurements.
- Benchmark LoRa-based localization systems based on the systematic grid-based sender movement described.
Strengths
- 4471 rows of measurements provide a substantial sample for model training.
- Includes ground truth (x,y) coordinates for each sender position, enabling supervised learning.
- Captures directed communication links between sender and four gateways, as well as inter-gateway links.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Data may reflect geographic bias inherent to the single sports hall environment.
- Freshness should be verified; last metadata update was 2026-05-26 14:03:57.
Provenance
- Source
- Harvard Dataverse
- Collection Method
- Systematic collection using a mobile sender moved on a grid within a sports hall, with four gateways at the corners.
- Geography
- A sports hall (specific location unknown).