Published December 9, 2025 | Version v1

Supporting material for "Towards Understanding Multimodal Transport Classification Using Features From RINEX Data Extracted From Android Phones" journal paper

  • 1. ROR icon Tampere University
  • 2. Ekin Labs Ltd
  • 3. ROR icon Tampere University of Technology
  • 4. Centrul IT pentru Stiinta si Tehnologie

Description

This is a comprehensive and anonymized dataset of features extracted from GNSS RINEX data from 409 user tracks collected by 18 volunteer users (user indices 1 to 7 and 9 to 19) during the years 2024 and 2025 across five European countries and under 10 transportation modes.  The features extracted from the Android data are detailed below, under the Data Description section. The data from user 8 was unusable, so it was removed from this dataset.  Volunteers used their own Android phones to run the GNSSlogger app and were asked to send each recorded track via the app’s semi-automatic email feature, including the transport mode in the email subject. Volunteers were instructed to record only one transport mode per track (e.g., to start a new track when switching from bus to walking or from walking to tram, etc.). Therefore, each track corresponds to a unique transportation mode, reflected in the file name. The data can serve, for example,  as useful training data for multi-modal classification using pseudorange-based information.

Details of the data found can be found in the Readme file uploaded in the same *zip file as the 409 tracks (the track data is provided in *csv format). The anonymous and volunteer data collectors are warmly thanked for their contributions.

How to cite this data:

Yelyzaveta Pervysheva, Jari Nurmi, Oana Cramariuc, and Elena Simona Lohan, "Supporting material for  “Towards Understanding  Multimodal Transport Classification Using Features From RINEX Data Extracted From Android Phones” journal paper", open-access dataset on Zenodo, DOI: 10.5281/zenodo.17864507

Files

MultiModal_data_forZenodo.zip

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Additional details

Funding

Research Council of Finland
CHIST-ERA ROBOSAT
Tampere University
Y-MOVE ECIU grant