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https://doi.org/10.21256/zhaw-3785| Publikationstyp: | Beitrag in Magazin oder Zeitung |
| Titel: | Applied data science : using machine learning for alarm verification : a novel alarm verification service applying various machine learning algorithms can identify false alarms |
| Autor/-in: | Stampfli, Jan Stockinger, Kurt |
| DOI: | 10.21256/zhaw-3785 |
| Erschienen in: | ERCIM News |
| Band(Heft): | 107 |
| Seite(n): | 10 |
| Erscheinungsdatum: | Okt-2016 |
| Verlag / Hrsg. Institution: | European Research Consortium for Informatics and Mathematics |
| ISSN: | 0926-4981 1564-0094 |
| Sprache: | Englisch |
| Schlagwörter: | Machine learning; Alarm verfication |
| Fachgebiet (DDC): | 006: Spezielle Computerverfahren |
| Zusammenfassung: | False alarms triggered by sensors of alarm systems are a frequent and costly inconvenience for the emergency services and owners of alarm systems. Around 90% of false alarms are caused by either technical failures such as network down times or human error. To remedy this problem, we develop a novel alarm verification service by leveraging the power of an alarm data warehouse. In addition, we apply various machine learning algorithms to identify false alarms. The goal of our system is to help human responders in their decision about whether or not to trigger costly intervention forces. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/7432 |
| Volltext Version: | Publizierte Version |
| Lizenz (gemäss Verlagsvertrag): | Keine Angabe |
| Departement: | School of Engineering |
| Organisationseinheit: | Institut für Informatik (InIT) |
| Publiziert im Rahmen des ZHAW-Projekts: | SAVE - Smart Alarms & Verified Events |
| Enthalten in den Sammlungen: | Publikationen School of Engineering |
Dateien zu dieser Ressource:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| 210931.pdf | 117.82 kB | Adobe PDF |  Öffnen/Anzeigen |
Zur Langanzeige
Stampfli, J., & Stockinger, K. (2016). Applied data science : using machine learning for alarm verification : a novel alarm verification service applying various machine learning algorithms can identify false alarms. ERCIM News, 107, 10. https://doi.org/10.21256/zhaw-3785
Stampfli, J. and Stockinger, K. (2016) ‘Applied data science : using machine learning for alarm verification : a novel alarm verification service applying various machine learning algorithms can identify false alarms’, ERCIM News, 107, p. 10. Available at: https://doi.org/10.21256/zhaw-3785.
J. Stampfli and K. Stockinger, “Applied data science : using machine learning for alarm verification : a novel alarm verification service applying various machine learning algorithms can identify false alarms,” ERCIM News, vol. 107, p. 10, Oct. 2016, doi: 10.21256/zhaw-3785.
STAMPFLI, Jan und Kurt STOCKINGER, 2016. Applied data science : using machine learning for alarm verification : a novel alarm verification service applying various machine learning algorithms can identify false alarms. ERCIM News. Oktober 2016. Bd. 107, S. 10. DOI 10.21256/zhaw-3785
Stampfli, Jan, and Kurt Stockinger. 2016. “Applied Data Science : Using Machine Learning for Alarm Verification : A Novel Alarm Verification Service Applying Various Machine Learning Algorithms Can Identify False Alarms.” ERCIM News 107 (October): 10. https://doi.org/10.21256/zhaw-3785.
Stampfli, Jan, and Kurt Stockinger. “Applied Data Science : Using Machine Learning for Alarm Verification : A Novel Alarm Verification Service Applying Various Machine Learning Algorithms Can Identify False Alarms.” ERCIM News, vol. 107, Oct. 2016, p. 10, https://doi.org/10.21256/zhaw-3785.
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