A deep-learning-based emergency alert system

Journal article


Kang, Byungseok and Choo, Hyunseung 2016. A deep-learning-based emergency alert system. ICT Express. https://doi.org/10.1016/j.icte.2016.05.001
AuthorsKang, Byungseok and Choo, Hyunseung
Abstract

Emergency alert systems serve as a critical link in the chain of crisis communication, and they are essential to minimize loss during emergencies. Acts of terrorism and violence, chemical spills, amber alerts, nuclear facility problems, weather-related emergencies, flu pandemics, and other emergencies all require those responsible such as government officials, building managers, and university administrators to be able to quickly and reliably distribute emergency information to the public. This paper presents our design of a deep-learning-based emergency warning system. The proposed system is considered suitable for application in existing infrastructure such as closed-circuit television and other monitoring devices. The experimental results show that in most cases, our system immediately detects emergencies such as car accidents and natural disasters.

KeywordsMachine learning; Deep learning; Emergency service selection
Year2016
JournalICT Express
PublisherElsevier
ISSN24059595
Digital Object Identifier (DOI)https://doi.org/10.1016/j.icte.2016.05.001
Web address (URL)http://hdl.handle.net/10545/623768
http://creativecommons.org/publicdomain/zero/1.0/
hdl:10545/623768
Publication dates21 May 2016
Publication process dates
Deposited23 May 2019, 10:54
Accepted04 May 2016
Rights

CC0 1.0 Universal

ContributorsSungkyunkwan University
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