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| Formato: | Artículo científico |
| Lenguaje: | en |
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Asociación Española para la Inteligencia Artificial
2017
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| Acceso en línea: | https://www.redalyc.org/articulo.oa?id=92549619002 |
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| _version_ | 1866817318348128256 |
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| author | Nuno Baeta |
| author_facet | Nuno Baeta |
| contents | Mining Users Mobility at Public Transportation Nuno Baeta Agnelo Fernandes João Ferreira Ingeniería Wi Fi GPS Tracking Knowledge In this research work we propose a new approach to estimate the number of passengers in a public transportation and determinate the users’ route path based on a passive approach without user intervention. The method is based on the probe requests of users mobile device through the collected data in wireless access point. This data is manipulated to extract the information about the numbers of users with mobile devices and track their route path and time. This data can be manipulated to extract useful knowledge related with users’ habits at public transportation and extract user mobility patterns. 2017 artículo científico 1137-3601 https://www.redalyc.org/articulo.oa?id=92549619002 en http://www.redalyc.org/revista.oa?id=925 Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial application/pdf Asociación Española para la Inteligencia Artificial Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial (España) Num.59 Vol.20 |
| format | Artículo científico |
| id | redalyc_92549619002 |
| language | en |
| publishDate | 2017 |
| publisher | Asociación Española para la Inteligencia Artificial |
| spellingShingle | Mining Users Mobility at Public Transportation Nuno Baeta Ingeniería Wi Fi GPS Tracking Knowledge Mining Users Mobility at Public Transportation Nuno Baeta Agnelo Fernandes João Ferreira Ingeniería Wi Fi GPS Tracking Knowledge In this research work we propose a new approach to estimate the number of passengers in a public transportation and determinate the users’ route path based on a passive approach without user intervention. The method is based on the probe requests of users mobile device through the collected data in wireless access point. This data is manipulated to extract the information about the numbers of users with mobile devices and track their route path and time. This data can be manipulated to extract useful knowledge related with users’ habits at public transportation and extract user mobility patterns. 2017 artículo científico 1137-3601 https://www.redalyc.org/articulo.oa?id=92549619002 en http://www.redalyc.org/revista.oa?id=925 Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial application/pdf Asociación Española para la Inteligencia Artificial Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial (España) Num.59 Vol.20 |
| title | Mining Users Mobility at Public Transportation |
| topic | Ingeniería Wi Fi GPS Tracking Knowledge |
| url | https://www.redalyc.org/articulo.oa?id=92549619002 |