Abstract

In recent years, wireless sensor networks (WSN) have shown success in distributed real-time signal processing systems. In collaborative signal processing environments, each sensor is responsible for extracting pertinent information from the surrounding environment and transmitting it to other sensors and/or to the main processing station. Often times, the sensors operate under a number of constraints, such as limited processing power and low bandwidth. In this paper we propose a collaborative signal processing framework that is implemented in an acoustic monitoring scenario. A low-complexity voice activity detector and a gender classifier are implemented on the Crossbow sensor motes. A series of experiments are presented that characterize the performance of the algorithms under varying SNR conditions and in different environments.

Original languageEnglish (US)
Title of host publication2006 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings
PagesIII1120-III1123
StatePublished - Dec 1 2006
Event2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006 - Toulouse, France
Duration: May 14 2006May 19 2006

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume3
ISSN (Print)1520-6149

Other

Other2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006
CountryFrance
CityToulouse
Period5/14/065/19/06

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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  • Cite this

    Berisha, V., Kwon, H., & Spanias, A. (2006). Real-time collaborative monitoring in wireless sensor networks. In 2006 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings (pp. III1120-III1123). [1660855] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 3).