Poster abstract: Online data cleaning in wireless sensor networks

Eiman Elnahrawy, Badri Nath

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

19 Scopus citations

Abstract

We present our ongoing work on data quality problems in sensor networks. Specifically, we deal with the problems of outliers, missing information, and noise. We propose an approach for modeling and online learning of spatio-temporal correlations in sensor networks. We utilize the learned correlations to discover outliers and recover missing information. We also propose a Bayesian approach for reducing the effect of noise on sensor data online.

Original languageEnglish (US)
Title of host publicationSenSys'03
Subtitle of host publicationProceedings of the First International Conference on Embedded Networked Sensor Systems
Pages294-295
Number of pages2
StatePublished - 2003
EventSenSys'03: Proceedings of the First International Conference on Embedded Networked Sensor Systems - Los Angeles, CA, United States
Duration: Nov 5 2003Nov 7 2003

Publication series

NameSenSys'03: Proceedings of the First International Conference on Embedded Networked Sensor Systems

Other

OtherSenSys'03: Proceedings of the First International Conference on Embedded Networked Sensor Systems
CountryUnited States
CityLos Angeles, CA
Period11/5/0311/7/03

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Keywords

  • Bayesian Theory
  • Fault-Tolerance
  • Noisy Sensors
  • Outliers

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