Visual Integration of Meteorological and Sensor Data for Identifying Suspicious Company Behavior

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FISHER, Brian, ed., Shixia LIU, ed., Tobias SCHRECK, ed.. 2017 IEEE Conference on Visual Analytics Science and Technology (VAST), Proceedings. Piscataway, NJ: IEEE, 2017, pp. 225-226. ISBN 978-1-5386-3163-8. Available under: doi: 10.1109/VAST.2017.8585436
Zusammenfassung

We present an approach developed in course of the VAST 2017 Mini-Challenge 2. To help the ornithologist Mitch to investigate the noxious gases emitted by the four companies south of the nature preserve, we employ a combination of interactive visualizations that allow for an exploration of the data. In this paper, we present our visual-interactive approach for analyzing suspicious patterns in the data. By taking the wind data into consideration, as well, our approach allows the retrieval of patterns in the chemical releases and identify key polluters.

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2017 IEEE Conference on Visual Analytics Science and Technology (VAST), 3. Okt. 2017 - 6. Okt. 2017, Phoenix, AZ
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ISO 690SEEBACHER, Daniel, Bruno SCHNEIDER, Michael BEHRISCH, 2017. Visual Integration of Meteorological and Sensor Data for Identifying Suspicious Company Behavior. 2017 IEEE Conference on Visual Analytics Science and Technology (VAST). Phoenix, AZ, 3. Okt. 2017 - 6. Okt. 2017. In: FISHER, Brian, ed., Shixia LIU, ed., Tobias SCHRECK, ed.. 2017 IEEE Conference on Visual Analytics Science and Technology (VAST), Proceedings. Piscataway, NJ: IEEE, 2017, pp. 225-226. ISBN 978-1-5386-3163-8. Available under: doi: 10.1109/VAST.2017.8585436
BibTex
@inproceedings{Seebacher2017Visua-44808,
  year={2017},
  doi={10.1109/VAST.2017.8585436},
  title={Visual Integration of Meteorological and Sensor Data for Identifying Suspicious Company Behavior},
  isbn={978-1-5386-3163-8},
  publisher={IEEE},
  address={Piscataway, NJ},
  booktitle={2017 IEEE Conference on Visual Analytics Science and Technology (VAST), Proceedings},
  pages={225--226},
  editor={Fisher, Brian and Liu, Shixia and Schreck, Tobias},
  author={Seebacher, Daniel and Schneider, Bruno and Behrisch, Michael}
}
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