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Finding dense locations in symbolic indoor tracking data: modeling, indexing, and processing / Tanvir Ahmed in Geoinformatica, vol 21 n° 1 (January - March 2017)  

Public [article]  inGeoinformatica > vol 21 n° 1 (January - March 2017) . - pp 119 - 150 Titre : Finding dense locations in symbolic indoor tracking data: modeling, indexing, and processing Type de document : Article/Communication Auteurs : Tanvir Ahmed, Auteur ; Toren Bach Pedersen, Auteur ; Hua Lu, Auteur Année de publication : 2017 Article en page(s) : pp 119 - 150 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] données spatiotemporelles [Termes IGN] géolocalisation [Termes IGN] index spatial [Termes IGN] positionnement en intérieur [Termes IGN] requête spatiale [Termes IGN] système de gestion de bases de données relationnelles Résumé : (auteur) Finding the dense locations in large indoor spaces is very useful for many applications such as overloaded area detection, security control, crowd management, indoor navigation, and so on. Indoor tracking data can be enormous and are not immediately ready for finding dense locations. This paper presents two graph-based models for constrained and semi-constrained indoor movement, respectively, and then uses the models to map raw tracking records into mapping records that represent object entry and exit times in particular locations. Subsequently, an efficient indexing structure called Hierarchical Dense Location Time Index (HDLT-Index) is proposed for indexing the time intervals of the mapping table, along with index construction, query processing, and pruning techniques. The HDLT-Index supports very efficient aggregate point, interval, and duration queries as well as dense location queries. A comprehensive experimental study with both real and synthetic data shows that the proposed techniques are efficient and scalable and outperforms RDBMSs significantly. Numéro de notice : A2017-026 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-016-0276-8 En ligne : http://dx.doi.org/10.1007/s10707-016-0276-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83977 [article]