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Modeling 911 emergency events in cuenca-ecuador using geo-spatial data

  • Universidad de Cuenca

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

We present several techniques for modeling emergency events using data from 911 emergency calls in the city of Cuenca-Ecuador. We apply three types of models. First, we use a probabilistic description of events using Gaussian kernels based on both, regular segmentation and mixture models, to represent the spatial distribution of occurrences. Second, we verify the qualitative relation of the clusters obtained with our kernel model with respect to the geo-political organization of the city. Finally, we develop an emergency model using a large dataset corresponding to the period January 1st 2015 through December 31st 2016 and test various data mining algorithms for prediction purposes. We verify the usefulness of our approach experimentally.

Original languageEnglish
Title of host publicationTechnology Trends - 4th International Conference, CITT 2018, Revised Selected Papers
EditorsMiguel Botto-Tobar, Mayra D’Armas, Miguel Zúñiga Sánchez, Miguel Zúñiga-Prieto, Guillermo Pizarro
PublisherSpringer Verlag
Pages564-577
Number of pages14
ISBN (Print)9783030055318
DOIs
StatePublished - 2019
Event4th International Conference on Technology Trends, CITT 2018 - Babahoyo, Ecuador
Duration: 29 Aug 201831 Aug 2018

Publication series

NameCommunications in Computer and Information Science
Volume895
ISSN (Print)1865-0929

Conference

Conference4th International Conference on Technology Trends, CITT 2018
Country/TerritoryEcuador
CityBabahoyo
Period29/08/1831/08/18

Keywords

  • 911 calls
  • Emergency calls
  • GMM
  • Kernel models

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