Online recognition of people's activities from raw GPS data: semantic trajectory data analysis [r-libre/934]

Boukhechba, Mehdi; Bouzouane, Abdenour; Bouchard, Bruno; Gouin-Vallerand, Charles et Giroux, Sylvain (2015). Online recognition of people's activities from raw GPS data: semantic trajectory data analysis. Dans Proceedings of the 8th ACM International Conference on Pervasive Technologies Related to Assistive Environments, (PETRAE 2015, Corfu, Greece, July 01 - 03). ACM. https://doi.org/10.1145/2769493.2769498

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Catégorie de document :	Communications dans des actes de congrès/colloques
Évaluation par un comité de lecture :	Oui
Étape de publication :	Publié
Résumé :	The widespread use of GPS devices leads to an increasing availability of people traces. The GPS trajectory of a moving object is a time stamped sequence of latitude and longitude coordinates. The analysis and extraction of knowledge from GPS trajectories is important for several applications domains, ranging from traffic management to advertisement and social studies. We present an approach capable of incrementally extracting semantic locations from people's trajectories and inferring the activity done by users. We associate the places visited by people during their movements to a meaningful human activities using a novel algorithm that cluster incrementally user's moves into different type of activities. Studies using GPS records from a confined spatio-temporal region demonstrate that the proposal is effective and is capable of inferring human activities without depleting the phone resources.
Adresse de la version officielle :	http://dl.acm.org/citation.cfm?id=2769498
Déposant:	Gouin-Vallerand, Charles
Responsable :	R-libre
Dépôt :	06 mai 2016 15:27
Dernière modification :	09 juin 2022 19:55

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