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dc.contributor.authorFernández Ares, Antonio Javier 
dc.contributor.authorGarcía Sánchez, Pedro Abelardo 
dc.contributor.authorArenas, M. G.
dc.contributor.authorMora, A. M.
dc.contributor.authorCastillo Valdivieso, Pedro Ángel 
dc.date.accessioned2020-04-20T11:53:46Z
dc.date.available2020-04-20T11:53:46Z
dc.date.issued2020-03-09
dc.identifier.citationFernández-Ares, A., García-Sánchez, P., Arenas, M. G., Mora, A. M., & Castillo-Valdivieso, P. A. (2020). Detection and Analysis of Anomalies in People Density and Mobility Through Wireless Smartphone Tracking. IEEE Access, 8, 54237-54253.es_ES
dc.identifier.urihttp://hdl.handle.net/10481/61384
dc.description.abstractOne 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.es_ES
dc.description.sponsorshipThis 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.es_ES
dc.language.isoenges_ES
dc.publisherIEEEes_ES
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectAnomaly detectiones_ES
dc.subjectDevice trackinges_ES
dc.subjectCrowd analysises_ES
dc.subjectSmart citieses_ES
dc.titleDetection and Analysis of Anomalies in People Density and Mobility Through Wireless Smartphone Trackinges_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.doi10.1109/ACCESS.2020.2979367


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