Opportunistic sensing: Unattended acoustic sensor selection using crowdsourcing models

Po Sen Huang, Mark Allan Hasegawa-Johnson, Wotao Yin, Thomas S Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Unattended wireless sensor networks have been widely used in many applications. This paper proposes automatic sensor selection methods based on crowdsourcing models in the Opportunistic Sensing framework, with applications to unattended acoustic sensor selection. Precisely, we propose two sensor selection criteria and solve them via greedy algorithm and quadratic assignment. Our proposed method achieves, on average, 5.64% higher accuracy than the traditional approach under sparse reliability conditions.

Original languageEnglish (US)
Title of host publication2012 IEEE International Workshop on Machine Learning for Signal Processing - Proceedings of MLSP 2012
DOIs
StatePublished - Dec 12 2012
Event2012 22nd IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2012 - Santander, Spain
Duration: Sep 23 2012Sep 26 2012

Publication series

NameIEEE International Workshop on Machine Learning for Signal Processing, MLSP
ISSN (Print)2161-0363
ISSN (Electronic)2161-0371

Other

Other2012 22nd IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2012
CountrySpain
CitySantander
Period9/23/129/26/12

Keywords

  • Cooperative Sensing
  • Crowdsourcing models
  • Opportunistic Sensing
  • Quadratic Assignment Problem
  • Unattended Sensor Networks

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Signal Processing

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  • Cite this

    Huang, P. S., Hasegawa-Johnson, M. A., Yin, W., & Huang, T. S. (2012). Opportunistic sensing: Unattended acoustic sensor selection using crowdsourcing models. In 2012 IEEE International Workshop on Machine Learning for Signal Processing - Proceedings of MLSP 2012 [6349815] (IEEE International Workshop on Machine Learning for Signal Processing, MLSP). https://doi.org/10.1109/MLSP.2012.6349815