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Distributed Feature Extraction for Event Identification

  • Teresa H. Ko
  • Nina M. Berry
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3295)

Abstract

An important component of ubiquitous computing is the ability to quickly sense the dynamic environment to learn context awareness in real-time. To pervasively capture detailed information of movements, we present a decentralized algorithm for feature extraction within a wireless sensor network. By approaching this problem in a distributed manner, we are able to work within the real constraint of wireless battery power and its effects on processing and network communications. We describe a hardware platform developed for low-power ubiquitous wireless sensing and a distributed feature extraction methodology which is capable of providing more information to the user of events while reducing power consumption. We demonstrate how the collaboration between sensor nodes can provide a means of organizing large networks into information-based clusters.

Keywords

Sensor Network Sensor Node Wireless Sensor Network Image Segmentation Image Sensor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Teresa H. Ko
    • 1
  • Nina M. Berry
    • 1
  1. 1.Embedded Reasoning InstituteSandia National LaboratoriesLivermoreUSA

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