AI advisor platform for disaster response based on big data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F44555601%3A13510%2F23%3A43896119" target="_blank" >RIV/44555601:13510/23:43896119 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1002/cpe.6215" target="_blank" >https://doi.org/10.1002/cpe.6215</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1002/cpe.6215" target="_blank" >10.1002/cpe.6215</a>
Alternative languages
Result language
angličtina
Original language name
AI advisor platform for disaster response based on big data
Original language description
In the past, the emergency responses to disasters such as fire outbreak accidents, accidents that require first aid were slow and not optimal. With human intellect, it was impractical to analyze vast amounts of data regarding the continuity of the numerous environmental changes and the correlation there may be with emergency responses based on past experiences with similar situations. Today, artificial intelligence is presented as a powerful tool to various organizations. Many have already made various attempts to apply this technology as an advisor for emergency response. This research expands on the practicality and effectiveness of utilizing AI as an advisory platform for disaster response based on the big-data, and also it designs an AI advisor platform for disaster response with big data-based algorithms. Finally AI advisor function are defined as part of the AI advisor platform, the voice recognition function, natural language processing function, big data coordination function.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Concurrency and Computation: Practice and Experience
ISSN
1532-0626
e-ISSN
1532-0634
Volume of the periodical
35
Issue of the periodical within the volume
16
Country of publishing house
US - UNITED STATES
Number of pages
8
Pages from-to
1-8
UT code for WoS article
000613948400001
EID of the result in the Scopus database
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