Multiple correspondence analysis of emergencies attended by integrated security services

Corral De Witt, Danilo, Carrera, Enrique V., Muñoz Romero, Sergio, Tepe, Kemal and Rojo Álvarez, José Luis (2019). Multiple correspondence analysis of emergencies attended by integrated security services. "Applied Sciences", v. 9 (n. 7); pp. 1-24. ISSN 2076-3417.


Title: Multiple correspondence analysis of emergencies attended by integrated security services
  • Corral De Witt, Danilo
  • Carrera, Enrique V.
  • Muñoz Romero, Sergio
  • Tepe, Kemal
  • Rojo Álvarez, José Luis
Item Type: Article
Título de Revista/Publicación: Applied Sciences
Date: 2019
ISSN: 2076-3417
Volume: 9
Freetext Keywords: Public-safety answering point, First-response institutions, Multiple correspondence analysis, ECU-911, Parzen windows, Bootstrap resampling
Faculty: E.T.S. de Ingenieros Informáticos (UPM)
Department: Otro
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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A public safety answering point (PSAP) receives thousands of security alerts and attends a similar number of emergencies every day, and all the information related to those events is saved to be post-processed and scrutinized. Visualization and interpretation of emergency data can provide fundamental feedback to the first-response institutions, to managers planning resource distributions, and to all the instances participating in the emergency-response cycle. This paper develops the application of multiple correspondence analysis (MCA) of emergency responses in a PSAP, with the objective of finding informative relationships among the different categories of registered and attended events. We propose a simple yet statistically meaningful method to scrutinize the variety of events and recorded information in conventional PSAPs. For this purpose, MCA is made on the categorical features of the available report forms, and a statistical description is achieved from it by combining bootstrap resampling and Parzen windowing, in order to provide the user with the most relevant factors, their significance, and a meaningful representation of the event grouping trends in a given database. We analyzed the case of the 911-emergency database from Quito, Ecuador, which includes 1,078,846 events during 2014. Individual analysis of the first-response institutions showed that there are groups with very related categories, whereas their joint analysis showed significant relationships among several types of events. This was the case for fire brigades, military, and municipal services attending large-scale forest fires, where they work in a combined way. Independence could be established among actions in other categories, which was the case for specific police events (as drug selling and distribution) or fire brigades events (as fire threats). We also showed that a very low number of factors can be enough to accurately represent the dynamics of frequent events.

Funding Projects

Government of Spain
Universidad Rey Juan Carlos
Procesado digital no lineal y aprendizaje estadístico con núcleos autocorrelación para aplicaciones en salud
Government of Spain
Universidad Rey Juan Carlos
Investigación traslacional y transferencia de un nuevo sistema de electrofisiología cardiaca no inavasiva de alta resolución
Government of Spain
Universidad de Valencia
Avances en métodos núcleo para datos estructurados
Madrid Regional Government
Programa Redes eléctricas inteligentes en la Comunidad de Madrid

More information

Item ID: 67131
DC Identifier:
OAI Identifier:
DOI: 10.3390/app9071396
Official URL:
Deposited by: Memoria Investigacion
Deposited on: 19 May 2021 06:26
Last Modified: 30 Nov 2022 09:00
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