Anomaly Detection on Live Water Pressure Data Stream

descriptionPublicationkeyboard_double_arrow_right Article , Conference object 01 Jan 2021Publisher:ZenodoJournal:SiKDD2021Funded by:EC | STAR, EC | ODEUROPA, EC | NAIADES

Authors: Gal Petkovšek; Matic Erznožnik; Klemen Kenda;

doi: 10.5281/zenodo.7691772 , 10.5281/zenodo.7691773

Anomaly Detection on Live Water Pressure Data Stream

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Abstract

We present the application of several anomaly detection algorithms to water pressure data streams. We evaluate their quality on unlabelled data sets using agreement rates. The applied algorithms are the Generative Adversarial Network (GAN), DBSCAN, Welford’s algorithm and Facebook Prophet. We found that GAN performed best.

Related Organizations

Josef Stefan Institut
Slovenia
Jožef Stefan International Postgraduate School
Slovenia
Jožef Stefan Institute
Slovenia

Keywords

water management, machine learning, anomaly detection

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