2022
DOI: 10.11144/javeriana.cvu15.simu
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Sistemas inteligentes de movilidad urbana en Río de Janeiro: una evaluación crítica

Abstract: El uso del potencial del big data presenta retos para la gestión de las ciudades, sobre todo cuando se introducen sistemas inteligentes en el sistema de movilidad que afectan la vida y los desplazamientos de las personas en las ciudades. El objetivo del presente análisis es evaluar los sistemas inteligentes de movilidad urbana de la ciudad de Río de Janeiro. La metodología parte del reconocimiento de datos de las aplicaciones de movilidad, sumados a datos del sistema de metro, tranvía y bicicletas compartidas,… Show more

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Cited by 2 publications
(1 citation statement)
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“…Research papers in Topic 2, which we labelled Human dynamics in spaces, mainly discuss the details and features of human travel activities, including travel mode, daily ridership, temporal dynamics, and transit usage. This stream of studies are conducted in various case cities across the globe, such as Beijing, China (D. , Seoul, Korea (Park & Chang, 2020), and Rio de Janeiro (Costa, 2022), etc. Event modeling (T3) is rather a niched research area that represents thematic studies on the early detection of major events from mobility activities (Aoki et al, 2021) or human's collective movement patterns during large-scale events (Fan & Stewart, 2021).…”
Section: Topic Detection Interpretation and Visualizationmentioning
confidence: 99%
“…Research papers in Topic 2, which we labelled Human dynamics in spaces, mainly discuss the details and features of human travel activities, including travel mode, daily ridership, temporal dynamics, and transit usage. This stream of studies are conducted in various case cities across the globe, such as Beijing, China (D. , Seoul, Korea (Park & Chang, 2020), and Rio de Janeiro (Costa, 2022), etc. Event modeling (T3) is rather a niched research area that represents thematic studies on the early detection of major events from mobility activities (Aoki et al, 2021) or human's collective movement patterns during large-scale events (Fan & Stewart, 2021).…”
Section: Topic Detection Interpretation and Visualizationmentioning
confidence: 99%