Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICDEW.2013.6547439
Title: RFID based vehicular networks for smart cities
Authors: Paul, J.
Malhotra, B.
Dale, S.
Qiang, M. 
Issue Date: 2013
Citation: Paul, J.,Malhotra, B.,Dale, S.,Qiang, M. (2013). RFID based vehicular networks for smart cities. Proceedings - International Conference on Data Engineering : 120-127. ScholarBank@NUS Repository. https://doi.org/10.1109/ICDEW.2013.6547439
Abstract: Monitoring the activities of vehicles in modern cities and urban areas has become imperative for solving the traffic related problems. Latest information about mobile vehicles, such as their identification (number plate), position, speed, and so on, are very important for smart traffic management solutions and business analytics. To that end, RFID tags (installed on vehicles) and readers (installed on roads) based traffic monitoring systems have gained a lot of attention due to their cost effectiveness. Usually the RFID readers are much costlier than the RFID tags, therefore, there is always a constraint on the number of RFID readers that can be deployed. This work explores the particular problem of locating suitable places in a road network for RFID readers that can capture the maximum amount of traffic data. To that end, the graph centrality measures are used to find the nodes with most connectivity. The underlying assumption is that the most connected nodes experience the most traffic flow. A new centrality measure is also proposed that is more suitable for analyzing the road networks than the existing graph centrality measures. The experimental results on real maps and data reveal that the newly proposed measure is very effective for analyzing the road networks. © 2013 IEEE.
Source Title: Proceedings - International Conference on Data Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/91328
ISBN: 9781467353021
ISSN: 10844627
DOI: 10.1109/ICDEW.2013.6547439
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

6
checked on Oct 15, 2018

Page view(s)

27
checked on Oct 19, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.