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Scientific Article details

Title Studying real traffic and mobility scenarios for a Smart City using a new monitoring and tracking system
ID_Doc 37438
Authors Fernández-Ares, A; Mora, AM; Arenas, MG; García-Sanchez, P; Romero, G; Rivas, V; Castillo, PA; Merelo, JJ
Title Studying real traffic and mobility scenarios for a Smart City using a new monitoring and tracking system
Year 2017
Published
DOI 10.1016/j.future.2016.11.021
Abstract This paper presents a novel mobility monitoring system and some of its applications to address problems that would be solved in a Smart City, such as the optimization of traffic flows in terms of trip-time and security (Smart Traffic), and the improvement of security or energetic issues inside buildings. The system tracks the movement of people and vehicles monitoring the radioelectric space, catching the WiFi and Bluetooth signals emitted by personal (smartphones) or on-board (hands-free) devices. A study has been conducted in four different real scenarios, i.e. with real data gathered by the system: two related with people's mobility (a public building and a discotheque); and two focused in traffic tracking (urban and intercity roads). The analysis has consisted on the application of different data mining techniques to extract useful knowledge, traffic forecasting methods to perform accurate predictions, and statistical analyses to model and validate the system reliability (comparing to other real data sources). The obtained results show the viability and utility of the system in all the cases, along with some of its multiple applications for solving different issues in a city. (C) 2016 Elsevier B.V. All rights reserved.
Author Keywords Smart Traffic; Transit indicators; Traffic forecast; Mobility analysis; Smart City; Internet of Things
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
EID WOS:000407983100014
WoS Category Computer Science, Theory & Methods
Research Area Computer Science
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