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Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-3785
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dc.contributor.authorStampfli, Jan-
dc.contributor.authorStockinger, Kurt-
dc.date.accessioned2018-06-28T09:51:43Z-
dc.date.available2018-06-28T09:51:43Z-
dc.date.issued2016-10-
dc.identifier.issn0926-4981de_CH
dc.identifier.issn1564-0094de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/7432-
dc.description.abstractFalse 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.de_CH
dc.language.isoende_CH
dc.publisherEuropean Research Consortium for Informatics and Mathematicsde_CH
dc.relation.ispartofERCIM Newsde_CH
dc.rightsNot specifiedde_CH
dc.subjectMachine learningde_CH
dc.subjectAlarm verficationde_CH
dc.subject.ddc006: Spezielle Computerverfahrende_CH
dc.titleApplied data science : using machine learning for alarm verification : a novel alarm verification service applying various machine learning algorithms can identify false alarmsde_CH
dc.typeBeitrag in Magazin oder Zeitungde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Informatik (InIT)de_CH
dc.identifier.doi10.21256/zhaw-3785-
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.start10de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.volume107de_CH
zhaw.webfeedDatalabde_CH
zhaw.funding.zhawSAVE - Smart Alarms & Verified Eventsde_CH
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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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