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Anomaly Detection in Data Streams: The Petrol Station Simulator

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Beyond Databases, Architectures and Structures. Advanced Technologies for Data Mining and Knowledge Discovery (BDAS 2015, BDAS 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 613))

Abstract

Developing anomaly detection systems requires diverse data for training and testing purposes. Real measurements are not necessarily reliable at this stage because it is almost impossible to find a diverse training set with exactly known characteristics. The petrol station simulator was designed to generate measurements that mimic real petrol station readings. The simulator produces datasets with exactly specified anomalies to be detected via anomaly detection system. The paper introduces foundations of the simulator with results. The discussion section presents future work in the area of stream data extraction and materialization in the Stream Data Warehouse.

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Acknowledgments

The authors would like to thank Professor Marcin Gorawski from Silesian University of Technology, Poland for support and mentoring, and undergraduate students Krzysztof Zagórski and Marek Bajorek for their collaboration during the implementation phase.

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Authors and Affiliations

  1. Faculty of Automatic Control, Electronics, and Computer Science, Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100, Gliwice, Poland

    Anna Gorawska & Krzysztof Pasterak

Authors
  1. Anna Gorawska
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  2. Krzysztof Pasterak
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Corresponding author

Correspondence to Anna Gorawska .

Editor information

Editors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Stanisław Kozielski

  2. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Dariusz Mrozek

  3. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Paweł Kasprowski

  4. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Bożena Małysiak-Mrozek

  5. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Daniel Kostrzewa

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Gorawska, A., Pasterak, K. (2016). Anomaly Detection in Data Streams: The Petrol Station Simulator. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds) Beyond Databases, Architectures and Structures. Advanced Technologies for Data Mining and Knowledge Discovery. BDAS BDAS 2015 2016. Communications in Computer and Information Science, vol 613. Springer, Cham. https://doi.org/10.1007/978-3-319-34099-9_57

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  • DOI: https://doi.org/10.1007/978-3-319-34099-9_57

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-34098-2

  • Online ISBN: 978-3-319-34099-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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