| Title |
Trajectory Data Analysis Over a Cloud-Based Framework for Smart City Analytics |
| ID_Doc |
41084 |
| Authors |
Cesario, E; Comito, C; Talia, D |
| Title |
Trajectory Data Analysis Over a Cloud-Based Framework for Smart City Analytics |
| Year |
2014 |
| Published |
|
| DOI |
10.1007/978-3-319-00491-4_8 |
| Abstract |
The chapter presents a Cloud-based framework that can be tailored to be used in different scenarios of urban planning and management occuring in Smart Cities. The focus is on the management of large-scale socio-geographic data obtained through the trajectories traced by smart objects. Our goal is to mine human activities and routines from this socio-geographic data in order to catch user's behaviour. To this aim, we introduce a methodology for trajectory pattern mining consisting in (a) finding frequent regions, more densely passed through ones, and (b) extracting trajectory patterns from those regions. Experimental evaluation shows that due to complexity and large data involved in the application scenario, the trajectory pattern mining process can take advantage from a parallel execution environment offered by a Cloud architecture. |
| Author Keywords |
|
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Book Citation Index – Science (BKCI-S) |
| EID |
WOS:000425684700009 |
| WoS Category |
Computer Science, Artificial Intelligence; Computer Science, Information Systems; Telecommunications |
| Research Area |
Computer Science; Telecommunications |
| PDF |
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