Research on moving-object data analysis has been recently fostered by the widespread diffusion of new techniques and systems for monitoring, collecting and storing loca- tion aware data, generated by a wealth of technological infrastructures, such as GPS positioning and wireless networks. These have made available massive repositories of spatio-temporal data recording human mobile activities, that call for suitable analytical methods, capable of enabling the development of innovative, location-aware applica- tions [3]. The M-Atlas is the evolution of the system presented in [5] allows to handle the whole knowledge discovery process from mobility data. The analysis capabilities of M-Atlas system have been applied onto a massive real life GPS dataset, obtained from 17,000 vehicles with on-board GPS receivers under a specific car insurance contract, tracked during one week of ordinary mobile activity in the urban area of the city of Milan; the dataset contains more than 2 million observations leading to a set of more than 200,000 trajectories.

Exploring real mobility data with M-Atlas

Trasarti R;Rinzivillo S;Pinelli F;Nanni M;Monreale A;Renso C;Pedreschi D;Giannotti F
2010

Abstract

Research on moving-object data analysis has been recently fostered by the widespread diffusion of new techniques and systems for monitoring, collecting and storing loca- tion aware data, generated by a wealth of technological infrastructures, such as GPS positioning and wireless networks. These have made available massive repositories of spatio-temporal data recording human mobile activities, that call for suitable analytical methods, capable of enabling the development of innovative, location-aware applica- tions [3]. The M-Atlas is the evolution of the system presented in [5] allows to handle the whole knowledge discovery process from mobility data. The analysis capabilities of M-Atlas system have been applied onto a massive real life GPS dataset, obtained from 17,000 vehicles with on-board GPS receivers under a specific car insurance contract, tracked during one week of ordinary mobile activity in the urban area of the city of Milan; the dataset contains more than 2 million observations leading to a set of more than 200,000 trajectories.
2010
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
978-3-642-15939-8
Database Management. Data mining
Data mining
Applications and ExpertSystems
Computational transportation science (CTS)
File in questo prodotto:
File Dimensione Formato  
prod_44365-doc_84551.pdf

non disponibili

Descrizione: Exploring real mobility data with M-Atlas
Tipologia: Versione Editoriale (PDF)
Dimensione 258.33 kB
Formato Adobe PDF
258.33 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/52897
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 8
  • ???jsp.display-item.citation.isi??? 4
social impact