A Spatio-Temporal Approach to Individual Mobility Modeling in On-Device Cognitive Computing Platforms

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AudienciaPúblico en generales_ES
CoberturaMéxicoes_ES
Fecha de ingreso2026-09-15T00:30:19Z
Fecha de publicación2019-01-01
ResumenThe increased availability of GPS-enabled devices makes possible to collect location data for mining purposes and to develop mobility-based services (MBS). For most of the MBSs, determining interesting locations and frequent Points of Interest (POIs) is of paramount importance to study the semantic of places visited by an individual and the mobility patterns as a spatio-temporal phenomenon. In this paper, we propose a novel approach that uses mobility-based services for on-device and individual-centered mobility understanding. Unlike existing approaches that use crowd data for cloud-assisted POI extraction, the proposed solution autonomously detects POIs and mobility events to incrementally construct a cognitive map (spatio-temporal model) of individual mobility suitable to constrained mobile platforms. In particular, we focus on detecting POIs and enter-exits events as the key to derive statistical properties for characterizing the dynamics of an individual’s mobility. We show that the proposed spatio-temporal map effectively extracts core features from the user-POI interaction that are relevant for analytics such as mobility prediction. We also demonstrate how the obtained spatio-temporal model can be exploited to assess the relevance of daily mobility routines. This novel cognitive and on-line mobility modeling contributes toward the distributed intelligence of IoT connected devices without strongly compromising energy.es_ES
Doihttps://doi.org/10.3390/s19183949es_ES
URIhttps://riuat.uat.edu.mx/handle/123456789/2262
Idiomaeses_ES
EditorialMDPI AGes_ES
RelaciónSensorses_ES
URL relacionadohttps://doi.org/10.3390/s19183949es_ES
DerechosAcceso abierto (Metadatos de producción científica)es_ES
Licenciahttp://purl.org/coar/access_right/c_abf2es_ES
FuenteSensors
TítuloA Spatio-Temporal Approach to Individual Mobility Modeling in On-Device Cognitive Computing Platformses_ES
TipoArtículoes_ES
ArbitradoHa sido Arbitradoes_ES
AutorPérez-Torres, Rafael
AutorTorres-Huitzil, César
AutorGaleana-Zapién, Hiram
AutorPérez-Torres, Rafaeles_ES
AutorTorres-Huitzil, Césares_ES
AutorGaleana-Zapién, Hirames_ES
InstituciónUniversidad Autónoma de Tamaulipas
InstituciónUniversidad Autónoma de Tamaulipases_ES
Número18es_ES
Rango de páginas3949es_ES
URL relacionadahttps://doi.org/10.3390/s19183949
Tipo de artículoIndexado
Tipo de artículoIndexadoes_ES
Volumen19es_ES

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