Smart Mobility Analytics: Inferring Transport Modes and Sustainability Metrics from GPS Data and Machine Learning
- DOI
- 10.3390/atmos17030246
- Published
- 2026-02-27
- Container
- Atmosphere
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/atmos17030246,
title = {Smart Mobility Analytics: Inferring Transport Modes and Sustainability Metrics from GPS Data and Machine Learning},
author = {Néstor Diego Rivera-Campoverde and Andrea Karina Bermeo Naula and Blanca del Valle Arenas Ramírez and Daniel Israel Ortega Rodas},
year = {2026},
journal = {Atmosphere},
doi = {10.3390/atmos17030246},
url = {https://doi.org/10.3390/atmos17030246}
}RIS
TY - JOUR TI - Smart Mobility Analytics: Inferring Transport Modes and Sustainability Metrics from GPS Data and Machine Learning AU - Néstor Diego Rivera-Campoverde AU - Andrea Karina Bermeo Naula AU - Blanca del Valle Arenas Ramírez AU - Daniel Israel Ortega Rodas PY - 2026 JO - Atmosphere DO - 10.3390/atmos17030246 UR - https://doi.org/10.3390/atmos17030246 ER -
APA
Rivera-Campoverde, N. D., Naula, A. K. B., Ramírez, B. D. V. A., & Rodas, D. I. O. (2026). Smart Mobility Analytics: Inferring Transport Modes and Sustainability Metrics from GPS Data and Machine Learning. Atmosphere. https://doi.org/10.3390/atmos17030246
Source records
- crossref · retrieved 2026-09-25T03:21:10.039Z