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Erschienen in: Fire Technology 2/2021

15.04.2020 | Letter to the Editor

Using Artificial Intelligence for Safe and Effective Wildfire Evacuations

verfasst von: Xilei Zhao, Ruggiero Lovreglio, Erica Kuligowski, Daniel Nilsson

Erschienen in: Fire Technology | Ausgabe 2/2021

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Excerpt

Wildfire is a growing global concern for rural and urban areas [1]. Statistics show that the intensity and negative consequences of wildfire have increased in recent decades creating serious challenges for fire and emergency services, as well as communities in the wildland-urban interface [2-4]. As an example, 85 people lost their lives in California’s Camp fire, which made 2018 the deadliest US wildfire year in a century. To reduce the life safety risk of wildfire and to enhance the safety of communities threatened by wildfire, it is important to understand the physical and social dynamics characterizing wildfires [5]. Such an understanding will help to improve the design of the built environment in communities (e.g. buildings and transportation infrastructure) and enhance emergency planning by incorporating actual household evacuation behaviour. This incorporation of novel knowledge on evacuation behaviour will ultimately facilitate safe and effective evacuation during wildfire emergencies. To address this challenge, several wildfire evacuation models have been proposed in the literature and a comprehensive review of the modelling approaches is provided in Ronchi et al. [4]. …

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Literatur
5.
Zurück zum Zitat Lovreglio R, Kuligoskwi E, Welpole E, Gwynne S (2019) A modelling framework for householder decision-making for wildfire emergencies. Int J Disaster Risk Reduct 41:101274CrossRef Lovreglio R, Kuligoskwi E, Welpole E, Gwynne S (2019) A modelling framework for householder decision-making for wildfire emergencies. Int J Disaster Risk Reduct 41:101274CrossRef
7.
Zurück zum Zitat Lindell MK, Perry RW (2004) Communicating environmental risk in multiethnic communities. Sage, Thousand Oaks Lindell MK, Perry RW (2004) Communicating environmental risk in multiethnic communities. Sage, Thousand Oaks
11.
Zurück zum Zitat Ronchi E, Gwynne SMV (2019) Computational evacuation modelling in wildfires. In: Manzello SL (ed) Encyclopedia of wildfires and wildland-urban interface (WUI) fires. Springer, New York Ronchi E, Gwynne SMV (2019) Computational evacuation modelling in wildfires. In: Manzello SL (ed) Encyclopedia of wildfires and wildland-urban interface (WUI) fires. Springer, New York
13.
Zurück zum Zitat Schneider P, Walters WP, Plowright AT, Sieroka N, Listgarten J, Goodnow RA Jr, Fisher J, Jansen JM, Duca JS, Rush TS, Zentgraf M, Hill JE, Krutoholow E, Kohler M, Blaney J, Funatsu K, Luebkemann C, Schneider G (2019) Rethinking drug design in the artificial intelligence era. Nat Rev Drug Discov. https://doi.org/10.1038/s41573-019-0050-3CrossRef Schneider P, Walters WP, Plowright AT, Sieroka N, Listgarten J, Goodnow RA Jr, Fisher J, Jansen JM, Duca JS, Rush TS, Zentgraf M, Hill JE, Krutoholow E, Kohler M, Blaney J, Funatsu K, Luebkemann C, Schneider G (2019) Rethinking drug design in the artificial intelligence era. Nat Rev Drug Discov. https://​doi.​org/​10.​1038/​s41573-019-0050-3CrossRef
Metadaten
Titel
Using Artificial Intelligence for Safe and Effective Wildfire Evacuations
verfasst von
Xilei Zhao
Ruggiero Lovreglio
Erica Kuligowski
Daniel Nilsson
Publikationsdatum
15.04.2020
Verlag
Springer US
Erschienen in
Fire Technology / Ausgabe 2/2021
Print ISSN: 0015-2684
Elektronische ISSN: 1572-8099
DOI
https://doi.org/10.1007/s10694-020-00979-x

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