Preprocessing in a tiered sensor network for habitat monitoring

  • Authors:

  • Hanbiao Wang;Deborah Estrin;Lewis Girod

  • Affiliations:

  • Computer Science Department, University of California, Los Angeles (UCLA), Los Angeles, CA;Computer Science Department, University of California, Los Angeles (UCLA), Los Angeles, CA;Computer Science Department, University of California, Los Angeles (UCLA), Los Angeles, CA

  • Venue:
  • EURASIP Journal on Applied Signal Processing
  • Year:
  • 2003

Quantified Score

Hi-index 0.00

Visualization

Abstract

We investigate task decomposition and collaboration in a two-tiered sensor network for habitat monitoring. The system recognizes and localizes a specified type of birdcalls. The system has a few powerful macronodes in the first tier, and many less powerful micronodes in the second tier. Each macronode combines data collected by multiple micronodes for target classification and localization. We describe two types of lightweight preprocessing which significantly reduce data transmission from micronodes to macronodes. Micronodes classify events according to their cross-zero rates and discard irrelevant events. Data about events of interest is reduced and compressed before being transmitted to macronodes for target localization. Preliminary experiments illustrate the effectiveness of event filtering and data reduction at micronodes.