@misc{10481/61384,
year = {2020},
month = {3},
url = {http://hdl.handle.net/10481/61384},
abstract = {One of the challenges of this century is to use the data that a smart-city provides to make
life easier for its inhabitants. Speci cally, within the area of urban mobility, the possibility of detecting
anomalies in the movement of pedestrians and vehicles is an issue of vital importance for the planning and
administration of a city. The aim of this paper is to propose a methodology to detect the movement of people
from the information transmitted by their smart mobile devices, analyze these data, and be able to detect
or recognize anomalies in their behavior. In order to validate this methodology, different experiments have
been carried out based on real data aiming to extract knowledge, as well as obtaining a characterisation of
the anomalies detected. The use of this methodology might help the city policy makers to better manage
their mobility and transport resources.},
organization = {This work was supported by in part by the Dirección General de Tráfico under Project SPIP2017-02116, in part by the Ministerio de
Ciencia, Innovación y Universidades under Grant RTI2018-102002-A-I00, in part by the Ministerio español de Economía y Competitividad
under Grant TIN2017-85727-C4-2-P, in part by the FEDER under Grant TEC2015-68752, and in part by the FEDER y Junta de Andalucía
under Project B-TIC-402-UGR18.},
publisher = {IEEE},
keywords = {Anomaly detection},
keywords = {Device tracking},
keywords = {Crowd analysis},
keywords = {Smart cities},
title = {Detection and Analysis of Anomalies in People Density and Mobility Through Wireless Smartphone Tracking},
doi = {10.1109/ACCESS.2020.2979367},
author = {Fernández Ares, Antonio Javier and García Sánchez, Pedro Abelardo and Arenas, M. G. and Mora, A. M. and Castillo Valdivieso, Pedro Ángel},
}