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    • 33-Issue 3
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    Visual Analysis of Time-Series Similarities for Anomaly Detection in Sensor Networks

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    Date
    2014
    Author
    Steiger, Martin
    Bernard, Jürgen
    Mittelstädt, Sebastian
    Lücke-Tieke, Hendrik
    Keim, Daniel
    May, Thorsten
    Kohlhammer, Jörn
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    Abstract
    We present a system to analyze time-series data in sensor networks. Our approach supports exploratory tasks for the comparison of univariate, geo-referenced sensor data, in particular for anomaly detection. We split the recordings into fixed-length patterns and show them in order to compare them over time and space using two linked views. Apart from geo-based comparison across sensors we also support different temporal patterns to discover seasonal effects, anomalies and periodicities. The methods we use are best practices in the information visualization domain. They cover the daily, the weekly and seasonal and patterns of the data. Daily patterns can be analyzed in a clustering-based view, weekly patterns in a calendar-based view and seasonal patters in a projection-based view. The connectivity of the sensors can be analyzed through a dedicated topological network view. We assist the domain expert with interaction techniques to make the results understandable. As a result, the user can identify and analyze erroneous and suspicious measurements in the network. A case study with a domain expert verified the usefulness of our approach.
    BibTeX
    @article {10.1111:cgf.12396,
    journal = {Computer Graphics Forum},
    title = {{Visual Analysis of Time-Series Similarities for Anomaly Detection in Sensor Networks}},
    author = {Steiger, Martin and Bernard, Jürgen and Mittelstädt, Sebastian and Lücke-Tieke, Hendrik and Keim, Daniel and May, Thorsten and Kohlhammer, Jörn},
    year = {2014},
    publisher = {The Eurographics Association and John Wiley and Sons Ltd.},
    ISSN = {1467-8659},
    DOI = {10.1111/cgf.12396}
    }
    URI
    http://dx.doi.org/10.1111/cgf.12396
    Collections
    • 33-Issue 3
    • EuroVis14: Eurographics Conference on Visualization

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    Eurographics Association copyright © 2013 - 2020 
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    Theme by @mire NV
    System hosted at  Graz University of Technology.
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