Public Transport Stops State Detection and Propagation - Warsaw Use Case

Marcin Luckner, Paweł Kobojek, Paweł Zawistowski


Publication of information on public transport in a form acceptable to third–party developers can improve a quality of services offered to the citizens. Usually, published data are limited to localisations of the stops and the schedules. However, a public transport model based on these data is incomplete without information about a current state of the stops. In this paper, we present a system that observes public sources of information on public transport such as Twitter feeds and official web pages hosted by the City of Warsaw. The incoming messages are parsed to extract information on events that concern public transport lines and stops. Extracted information allows us to detect a current state of the stops and to create linguistically independent and spatial oriented information in Geography Markup Language format that can be published using a web service. The system has been tested on real data from Warsaw district and the suburban zones.


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Paper Citation

in Harvard Style

Luckner M., Kobojek P. and Zawistowski P. (2017). Public Transport Stops State Detection and Propagation - Warsaw Use Case . In Proceedings of the 6th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS, ISBN 978-989-758-241-7, pages 235-241. DOI: 10.5220/0006305102350241

in Bibtex Style

author={Marcin Luckner and Paweł Kobojek and Paweł Zawistowski},
title={Public Transport Stops State Detection and Propagation - Warsaw Use Case},
booktitle={Proceedings of the 6th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,},

in EndNote Style

JO - Proceedings of the 6th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,
TI - Public Transport Stops State Detection and Propagation - Warsaw Use Case
SN - 978-989-758-241-7
AU - Luckner M.
AU - Kobojek P.
AU - Zawistowski P.
PY - 2017
SP - 235
EP - 241
DO - 10.5220/0006305102350241