Publication Details
A Unified Approach to Real-Time Public Transport Data Processing
Public Transport, Big Data Processing, Big Data Visualisation, GTFS
The use of real operations data is essential for the planning and management of
modern public transport systems. With the expansion of universal formats for
describing the structure of public transport systems, such as GTFS or Transmodel,
the use of these data has expanded far beyond the public transport domain. On the
other hand, the effort to use these data encounters the problem of its
processing, storage and integration with the structure of the transport system
due to the volume and speed of data generation from real operations. These
problems are even more evident in the case of further use of these data as inputs
for machine learning, or data mining, where integration of data from different
systems into a single model is necessary. The purpose of this paper was to design
a method by the which big data from real operations could be integrated with the
changing structure of the transport system so that this data could be stored long
term without loss of granularity, or entropy value. As a result, we proposed
a data model with big data transformation algorithm, whose functionality has been
verified in testing over the public transport system of the second largest city
in the Czech Republic.
@inproceedings{BUT188364,
author="Juraj {Lazúr} and Jiří {Hynek} and Tomáš {Hruška}",
title="A Unified Approach to Real-Time Public Transport Data Processing",
booktitle="Lecture Notes in Networks and Systems",
year="2024",
series="Lecture Notes in Networks and Systems",
journal="Lecture Notes in Networks and Systems",
volume="2024",
number="989",
pages="86--95",
publisher="Springer Nature Switzerland AG",
address="Cham",
doi="10.1007/978-3-031-60227-6\{_}8",
isbn="978-3-031-60226-9",
issn="2367-3370",
url="https://www.fit.vut.cz/research/publication/13127/"
}