Exportar Publicação

A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Baeta, N., Fernandes, A. & Ferreira, J. (2017). Mining users mobility at public transportation. Inteligencia Artificial. 20 (59), 32-41
Exportar Referência (IEEE) 
N. Baeta et al.,  "Mining users mobility at public transportation", in Inteligencia Artificial, vol. 20, no. 59, pp. 32-41, 2017
Exportar BibTeX 
@article{baeta2017_1775872130391,
	author = "Baeta, N. and Fernandes, A. and Ferreira, J.",
	title = "Mining users mobility at public transportation",
	journal = "Inteligencia Artificial",
	year = "2017",
	volume = "20",
	number = "59",
	doi = "10.4114/intartif.vol20iss59pp32-41",
	pages = "32-41",
	url = "http://journal.iberamia.org/index.php/intartif/article/view/22"
}
Exportar RIS 
TY  - JOUR
TI  - Mining users mobility at public transportation
T2  - Inteligencia Artificial
VL  - 20
IS  - 59
AU  - Baeta, N.
AU  - Fernandes, A.
AU  - Ferreira, J.
PY  - 2017
SP  - 32-41
SN  - 1137-3601
DO  - 10.4114/intartif.vol20iss59pp32-41
UR  - http://journal.iberamia.org/index.php/intartif/article/view/22
AB  - 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.



ER  -