Using vehicular sensor networks for mobile surveillance

Kun Chan Lan; Chien Ming Chou; Han Yi Wang

doi:10.1109/VTCFall.2012.6398919

Using vehicular sensor networks for mobile surveillance

Kun Chan Lan, Chien Ming Chou, Han Yi Wang

Department of Computer Science and Information Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

8 Citations (Scopus)

Abstract

Mobile surveillance has been recently proposed as a replacement for traditional road-side surveillance system. One important aspect of a mobile surveillance system is to decide what the events of interest are. In this work, we adopt the concept of participatory sensing for mobile surveillance by involving a human into the loop of data collection. We introduce a virtual credit based mechanism to motivate the participants to collect data and share their bandwidth. Finally, we use a large-scale real- world vehicle trace to evaluate the feasibility of our proposed framework.

Original language	English
Title of host publication	2012 IEEE Vehicular Technology Conference, VTC Fall 2012 - Proceedings
DOIs	https://doi.org/10.1109/VTCFall.2012.6398919
Publication status	Published - 2012 Dec 1
Event	76th IEEE Vehicular Technology Conference, VTC Fall 2012 - Quebec City, QC, Canada Duration: 2012 Sep 3 → 2012 Sep 6

Publication series

Name	IEEE Vehicular Technology Conference
ISSN (Print)	1550-2252

Other

Other	76th IEEE Vehicular Technology Conference, VTC Fall 2012
Country	Canada
City	Quebec City, QC
Period	12-09-03 → 12-09-06

All Science Journal Classification (ASJC) codes

Computer Science Applications
Electrical and Electronic Engineering
Applied Mathematics

Access to Document

10.1109/VTCFall.2012.6398919

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abstract = "Mobile surveillance has been recently proposed as a replacement for traditional road-side surveillance system. One important aspect of a mobile surveillance system is to decide what the events of interest are. In this work, we adopt the concept of participatory sensing for mobile surveillance by involving a human into the loop of data collection. We introduce a virtual credit based mechanism to motivate the participants to collect data and share their bandwidth. Finally, we use a large-scale real- world vehicle trace to evaluate the feasibility of our proposed framework.",

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