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Fault Detection in Sensor Network Using DBSCAN and Statistical Models

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 247)

Abstract

In any sensor network one of the major challenges is to distinguish between the expected data and unexpected or faulty data. In this paper we have proposed a fault detection technique using DBSCAN and statistical model. DBSCAN is used to cluster the similar data and detect the outliers whereas statistical model is used to build a model to represent the expected behaviour of the sensor nodes. Using the expected behaviour model we have detected the faults in the data. Our experimental results on Intel Berkeley research lab dataset shows that faults have been successfully detected.

Keywords

Fault detection DBSCAN Statistical model Sensor Network 

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References

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department Of P.G Studies and Research in Computer ScienceMangalore UniversityMangaloreIndia

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