IWARN: A people-centered approach for early warning

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dc.contributor.author Díaz, Paloma
dc.contributor.author Sánchez de Francisco, Mónica
dc.contributor.author Onorati, Teresa
dc.contributor.author Montero Montes, Álvaro
dc.contributor.author Aedo Cuevas, Ignacio
dc.date.accessioned 2022-04-06T08:52:30Z
dc.date.available 2022-04-06T08:52:30Z
dc.date.issued 2022-01-03
dc.identifier.bibliographicCitation P. Díaz, M. Sánchez-Francisco, T. Onorati, Á. Montero, I. Aedo, "IWARN: A people-centered approach for early warning", presentada en 55th Annual Hawaii International Conference on System Sciences, Hawaii, January 3-7, 2022. [En línea]. Disponible en: http://hdl.handle.net/10125/79639
dc.identifier.isbn 978-0-9981331-5-7
dc.identifier.issn https://doi.org/10.24251/HICSS.2022.306
dc.identifier.uri http://hdl.handle.net/10016/34535
dc.description.abstract Early warning is the activity of the mitigation phase concerned with monitoring precursors of a potential hazard to decide whether it is evolving to real risk and eventually initiate an early response. The first step consists of collecting updated and reliable data to support situational awareness from emergency operators. Data-centered Early Warning Systems (EWS) are focused on gathering data and run simulations to support decision-makers. A more sustainable approach consists of a people-centered EWS that takes profit from citizens who act as intelligent sensors collecting and sharing purposeful information. This people-centered approach can contribute to raising community awareness of the local environment and its vulnerabilities. In this paper, we introduce iWarn, a system relying upon mobile to integrate citizens in this process. The system has been developed following an action research approach to involve different stakeholders, including professionals, volunteers and citizens.
dc.description.sponsorship This work is partly funded by “Comunidad de Madrid en el marco del convenio plurianual con la Universidad Carlos III Madrid en su línea de actuación Excelencia para el Profesorado Universitario-V Plan Regional de Investigación Científica e Innovación Tecnológica 2016-2020” the Spanish Ministry of Economy and Competitiveness Project TIN2016-77690-R “PACE.
dc.language.iso eng
dc.publisher Universidad De Hawaii
dc.rights © HICSS, 2022
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other disaster information, resilience for emergency and crisis technologies
dc.subject.other mobile technology
dc.subject.other crisis informatics
dc.subject.other citizen participation
dc.title IWARN: A people-centered approach for early warning
dc.type conferenceObject
dc.relation.publisherversion http://hdl.handle.net/10125/79639
dc.subject.eciencia Informática
dc.rights.accessRights openAccess
dc.relation.projectID Gobierno de España. TIN2016-77690-R
dc.type.version publishedVersion
dc.relation.eventdate 2022-01-03
dc.relation.eventplace ESTADOS UNIDOS DE AMERICA
dc.relation.eventtitle 55rd Annual Hawaii International Conference on System Sciences (HICSS 55)
dc.relation.eventtype proceeding
dc.identifier.publicationfirstpage 2451
dc.identifier.publicationlastpage 2460
dc.identifier.publicationtitle Proceedings of the 55th Hawaii International Conference on System Sciences
dc.identifier.uxxi CC/0000033002
dc.contributor.funder Comunidad de Madrid
dc.contributor.funder Ministerio de Economía y Competitividad (España)
dc.contributor.funder Universidad Carlos III de Madrid
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