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A Bayesian framework for the automated online assessment of sensor data quality

Citation

Smith, D and Timms, G and de Souza, P and D'Este, C, A Bayesian framework for the automated online assessment of sensor data quality, Sensors, 12, (7) pp. 9476-9501. ISSN 1424-8220 (2012) [Refereed Article]


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Licensed under Creative Commons Attribution 3.0 Unported (CC BY 3.0) http://creativecommons.org/licenses/by/3.0/

DOI: doi:10.3390/s120709476

Abstract

Online automated quality assessment is critical to determine a sensor’s fitness for purpose in real-time applications. A Dynamic Bayesian Network (DBN) framework is proposed to produce probabilistic quality assessments and represent the uncertainty of sequentially correlated sensor readings. This is a novel framework to represent the causes, quality state and observed effects of individual sensor errors without imposing any constraints upon the physical deployment or measured phenomenon. It represents the casual relationship between quality tests and combines them in a way to generate uncertainty estimates of samples. The DBN was implemented for a particular marine deployment of temperature and conductivity sensors in Hobart, Australia. The DBN was shown to offer a substantial average improvement (34%) in replicating the error bars that were generated by experts when compared to a fuzzy logic approach.

Item Details

Item Type:Refereed Article
Keywords:online filtering, automated, quality assessment, sensors, dynamic Bayesian networks
Research Division:Information and Computing Sciences
Research Group:Information Systems
Research Field:Information Systems not elsewhere classified
Objective Division:Environment
Objective Group:Ecosystem Assessment and Management
Objective Field:Ecosystem Assessment and Management of Marine Environments
Author:de Souza, P (Professor Paulo de Souza Junior)
ID Code:78644
Year Published:2012
Web of Science® Times Cited:11
Deposited By:Information and Communication Technology
Deposited On:2012-07-13
Last Modified:2017-11-20
Downloads:420 View Download Statistics

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