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Proceedings Paper

An algorithm for monitoring the traffic on a less-travelled road using multi-modal sensor suite
Author(s): Thyagaraju Damarla; Gary Chatters; Brian Liss; Hao Vu; James M. Sabatier
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Paper Abstract

We conducted an experiment to correlate the information gathered by a suite of hard sensors with the information on social networks such as Twitter, Facebook, etc. The experiment consisting of monitoring traffic on a well- traveled road and on a road inside a facility. The sensors suite selected mainly consists of sensors that require low power for operation and last a longtime. The output of each sensor is analyzed to classify the targets as ground vehicles, humans, and airborne targets. The algorithm is also used to count the number of targets belonging to each type so the sensor can store the information for anomaly detection. In this paper, we describe the classifier algorithms used for acoustic, seismic, and passive infrared (PIR) sensor data.

Paper Details

Date Published: 10 June 2014
PDF: 7 pages
Proc. SPIE 9079, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR V, 90790F (10 June 2014); doi: 10.1117/12.2050318
Show Author Affiliations
Thyagaraju Damarla, U.S. Army Research Lab. (United States)
Gary Chatters, U.S. Army Research Lab. (United States)
Brian Liss, U.S. Army Research Lab. (United States)
Hao Vu, U.S. Army Research Lab. (United States)
James M. Sabatier, Univ. of Mississippi (United States)


Published in SPIE Proceedings Vol. 9079:
Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR V
Michael A. Kolodny, Editor(s)

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