Preprocessing in a Tiered Sensor Network for Habitat Monitoring

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 macrono...

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Bibliographic Details
Main Authors: Hanbiao Wang, Deborah Estrin, Lewis Girod
Format: Article
Language:English
Published: SpringerOpen 2003-03-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
Online Access:http://dx.doi.org/10.1155/S1110865703212087
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author Hanbiao Wang
Deborah Estrin
Lewis Girod
author_facet Hanbiao Wang
Deborah Estrin
Lewis Girod
author_sort Hanbiao Wang
collection DOAJ
description 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.
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spelling doaj.art-139180e805bf4b48a9f198d10312c9122022-12-22T03:09:16ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61721687-61802003-03-0120034392401Preprocessing in a Tiered Sensor Network for Habitat MonitoringHanbiao WangDeborah EstrinLewis GirodWe 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.http://dx.doi.org/10.1155/S1110865703212087sensor networkcollaborative signal processingtiered architectureclassificationdata reductiondata
spellingShingle Hanbiao Wang
Deborah Estrin
Lewis Girod
Preprocessing in a Tiered Sensor Network for Habitat Monitoring
EURASIP Journal on Advances in Signal Processing
sensor network
collaborative signal processing
tiered architecture
classification
data reduction
data
title Preprocessing in a Tiered Sensor Network for Habitat Monitoring
title_full Preprocessing in a Tiered Sensor Network for Habitat Monitoring
title_fullStr Preprocessing in a Tiered Sensor Network for Habitat Monitoring
title_full_unstemmed Preprocessing in a Tiered Sensor Network for Habitat Monitoring
title_short Preprocessing in a Tiered Sensor Network for Habitat Monitoring
title_sort preprocessing in a tiered sensor network for habitat monitoring
topic sensor network
collaborative signal processing
tiered architecture
classification
data reduction
data
url http://dx.doi.org/10.1155/S1110865703212087
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AT deborahestrin preprocessinginatieredsensornetworkforhabitatmonitoring
AT lewisgirod preprocessinginatieredsensornetworkforhabitatmonitoring