DocumentCode :
715692
Title :
Quality of information-aware real-time traffic flow analysis and reporting
Author :
Mukherjee, Manisha ; Edwards, James ; Kwon, Heesung ; La Porta, Thomas F.
fYear :
2015
fDate :
23-27 March 2015
Firstpage :
69
Lastpage :
74
Abstract :
In this paper we present a framework for Quality of Information (QoI)-aware networking. QoI quantifies how useful a piece of information is for a given query or application. Herein, we present a general QoI model, as well as a specific example instantiation that carries throughout the rest of the paper. In this model, we focus on the tradeoffs between precision and accuracy. As a motivating example, we look at traffic video analysis. We present simple algorithms for deriving various traffic metrics from video, such as vehicle count and average speed. We implement these algorithms both on a desktop workstation and less-capable mobile device. We then show how QoI-awareness enables end devices to make intelligent decisions about how to process queries and form responses, such that huge bandwidth savings are realized.
Keywords :
mobile computing; traffic information systems; video signal processing; QoI; average speed; bandwidth savings; desktop workstation; end devices; form responses; information-aware real-time traffic flow analysis; mobile device; quality of information-aware networking; traffic metrics; traffic video analysis; vehicle count; Accuracy; Cameras; Image edge detection; Quality of service; Sensors; Streaming media; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pervasive Computing and Communication Workshops (PerCom Workshops), 2015 IEEE International Conference on
Conference_Location :
St. Louis, MO
Type :
conf
DOI :
10.1109/PERCOMW.2015.7133996
Filename :
7133996
Link To Document :
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