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
| Authors | Kang, 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. |
| Keywords | Machine learning; Deep learning; Emergency service selection |
| Year | 2016 |
| Journal | ICT Express |
| Publisher | Elsevier |
| ISSN | 24059595 |
| 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 dates | 21 May 2016 |
| Publication process dates | |
| Deposited | 23 May 2019, 10:54 |
| Accepted | 04 May 2016 |
| Rights | CC0 1.0 Universal |
| Contributors | Sungkyunkwan University |
| File | File Access Level Open |
| File | File Access Level Open |
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