Análise da Mobilidade Humana em Eventos de Larga Escala baseada em Chamadas de Telefones Celulares
Abstract
The analysis of the usage of mobile phone networks can help cellphone carriers to evolve and improve their services, as well as foster the well-being of our society with more "intelligent" services based on human mobility patterns. This work analyzes human mobility during different types of largescale events, specifically soccer matches and New Year's celebrations, using a methodology recently proposed by the authors. Human mobility is analyzed in terms of number of cellphone calls, their inter-arrival and inter-departure times, and their durations during these events. We also make use of heatmaps to analyze the displacement patterns of participants around the time and geographical area of the event. Our results could be used to improve the understanding of human mobility in urban areas during large-scale events.References
Bagrow, J. P., Wang, D., e Barabási, A.-L. (2011). Collective response of human populations to large-scale emergencies. PLoS ONE, 6(3):e17680.
Balcan, D., Colizza, V., Gonçalves, B., Hu, H., Ramasco, J. J., e Vespignani, A. (2009). Multiscale mobility networks and the spatial spreading of infectious diseases. Proceedings of the National Academy of Sciences, 106(51):21484–21489.
Batty, M., Desyllas, J., e Duxbury, E. (2003). The discrete dynamics of small-scale spatial events: agentbased models of mobility in carnivals and street parades. International Journal of Geographical Information Science, 17(7):673–697.
Bleicher, A. (2012). The on-demand olympics. IEEE Spectrum, 49(7):9–10.
Calabrese, F., Pereira, F., Di Lorenzo, G., Liu, L., e Ratti, C. (2010). The geography of taste: Analyzing cellphone mobility and social events. Em Floréen, P., Krüger, A., e Spasojevic, M., editors, Pervasive Computing, volume 6030 of Lecture Notes in Computer Science, pág. 22–37. Springer Berlin/Heidelberg.
Candia, J., González, M. C., Wang, P., Schoenharl, T., Madey, G., e Barabási, A.-L. (2008). Uncovering individual and collective human dynamics from mobile phone records. Journal of Physics A: Mathematical and Theoretical, 41(22):224015.
González, M. C., Hidalgo, C. A., e Barabási, A.-L. (2008). Understanding individual human mobility patterns. Nature, 453:779–782.
Google Maps (2012). Google maps javascript api v3.
Morlot, F., Elayoubi, S. E., e Baccelli, F. (2010). An interaction-based mobility model for dynamic hot spot analysis. Em Proceedings of the 29th conference on Information communications, INFOCOM’10, pág. 2294–2302, Piscataway, NJ, USA. IEEE Press.
Song, C., Qu, Z., Blumm, N., e Barabási, A.-L. (2010). Limits of predictability in human mobility. Science, 327(5968):1018–1021.
Soper, D. (2012). Is human mobility tracking a good idea? Communications of the ACM, 55(4):35–37.
Toole, J. L., Ulm, M., González, M. C., e Bauer, D. (2012). Inferring land use from mobile phone activity. Em Proceedings of the ACM SIGKDD International Workshop on Urban Computing, UrbComp ’12, pág. 1–8, New York, NY, USA. ACM.
Xavier, F. H. Z., Silveira, L. M., Almeida, J. M., Ziviani, A., Malab, C. H. S., e Marques-Neto, H. (2012). Analyzing the workload dynamics of a mobile phone network in large scale events. Em Proceedings of the UrbaNe Workshop – ACM CoNEXT 2012.
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Balcan, D., Colizza, V., Gonçalves, B., Hu, H., Ramasco, J. J., e Vespignani, A. (2009). Multiscale mobility networks and the spatial spreading of infectious diseases. Proceedings of the National Academy of Sciences, 106(51):21484–21489.
Batty, M., Desyllas, J., e Duxbury, E. (2003). The discrete dynamics of small-scale spatial events: agentbased models of mobility in carnivals and street parades. International Journal of Geographical Information Science, 17(7):673–697.
Bleicher, A. (2012). The on-demand olympics. IEEE Spectrum, 49(7):9–10.
Calabrese, F., Pereira, F., Di Lorenzo, G., Liu, L., e Ratti, C. (2010). The geography of taste: Analyzing cellphone mobility and social events. Em Floréen, P., Krüger, A., e Spasojevic, M., editors, Pervasive Computing, volume 6030 of Lecture Notes in Computer Science, pág. 22–37. Springer Berlin/Heidelberg.
Candia, J., González, M. C., Wang, P., Schoenharl, T., Madey, G., e Barabási, A.-L. (2008). Uncovering individual and collective human dynamics from mobile phone records. Journal of Physics A: Mathematical and Theoretical, 41(22):224015.
González, M. C., Hidalgo, C. A., e Barabási, A.-L. (2008). Understanding individual human mobility patterns. Nature, 453:779–782.
Google Maps (2012). Google maps javascript api v3.
Morlot, F., Elayoubi, S. E., e Baccelli, F. (2010). An interaction-based mobility model for dynamic hot spot analysis. Em Proceedings of the 29th conference on Information communications, INFOCOM’10, pág. 2294–2302, Piscataway, NJ, USA. IEEE Press.
Song, C., Qu, Z., Blumm, N., e Barabási, A.-L. (2010). Limits of predictability in human mobility. Science, 327(5968):1018–1021.
Soper, D. (2012). Is human mobility tracking a good idea? Communications of the ACM, 55(4):35–37.
Toole, J. L., Ulm, M., González, M. C., e Bauer, D. (2012). Inferring land use from mobile phone activity. Em Proceedings of the ACM SIGKDD International Workshop on Urban Computing, UrbComp ’12, pág. 1–8, New York, NY, USA. ACM.
Xavier, F. H. Z., Silveira, L. M., Almeida, J. M., Ziviani, A., Malab, C. H. S., e Marques-Neto, H. (2012). Analyzing the workload dynamics of a mobile phone network in large scale events. Em Proceedings of the UrbaNe Workshop – ACM CoNEXT 2012.
283
Published
2013-07-23
How to Cite
XAVIER, Faber Henrique Z.; SILVEIRA, Lucas M.; ALMEIDA, Jussara M.; ZIVIANI, Artur; MALAB, Carlos Henrique; MARQUES-NETO, Humberto T..
Análise da Mobilidade Humana em Eventos de Larga Escala baseada em Chamadas de Telefones Celulares. In: INTEGRATED SOFTWARE AND HARDWARE SEMINAR (SEMISH), 40. , 2013, Maceió.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2013
.
p. 272-283.
ISSN 2595-6205.
