Anomaly Detection in Emergency Call Data - the First Step to the Intelligent Emergency Call System Management

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Anomaly Detection in Emergency Call Data - the First Step to the Intelligent Emergency Call System Management

Popis výsledku v původním jazyce

A collaborative Emergency call taking information system in the Czech Republic processes calls on the European 112 emergency number. Amounts of various incident records are stored in its databases. The data can be used for mining spatial and temporal anomalies. When such an anomalous situation is detected so that the system could suffer from local or temporal performance decrease, either a human, or an automatic management module could take measures to reconfigure the system traffic and balance its load. In this paper we describe a method of knowledge discovery and visualization with respect to the emergency call taking information system database characteristics. The method is based on Kohonen Self Organizing Map (SOM) algorithm. Transformations of categorical attributes into numeric values are proposed to prepare training set appropriate for successful SOM generation.

Název v anglickém jazyce

Anomaly Detection in Emergency Call Data - the First Step to the Intelligent Emergency Call System Management

Popis výsledku anglicky

A collaborative Emergency call taking information system in the Czech Republic processes calls on the European 112 emergency number. Amounts of various incident records are stored in its databases. The data can be used for mining spatial and temporal anomalies. When such an anomalous situation is detected so that the system could suffer from local or temporal performance decrease, either a human, or an automatic management module could take measures to reconfigure the system traffic and balance its load. In this paper we describe a method of knowledge discovery and visualization with respect to the emergency call taking information system database characteristics. The method is based on Kohonen Self Organizing Map (SOM) algorithm. Transformations of categorical attributes into numeric values are proposed to prepare training set appropriate for successful SOM generation.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2009

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2009 INTERNATIONAL CONFERENCE ON INTELLIGENT NETWORKING AND COLLABORATIVE SYSTEMS (INCOS 2009)

ISBN

978-1-4244-5165-4

ISSN

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e-ISSN

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Počet stran výsledku

7

Strana od-do

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Název nakladatele

IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA

Místo vydání

NEW YORK

Místo konání akce

Open Univ Catalonia, Barcelona, SPAIN

Datum konání akce

4. 11. 2009

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000289914800034