Analyzing heatstroke patients in 2020 using Emergency Big Data
22nd IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2021-Fall
; : 56-61, 2021.
Article
in English
| Scopus | ID: covidwho-1741259
ABSTRACT
In this study, we conducted a multifaceted analysis of heatstroke cases using the emergency transported big data in Kobe City, and discovered the characteristics of heatstroke incidents in Kobe City in 2020 that differed from previous years. As a result of the analysis, it was found that the peak period of WBGT in 2020 was later than usual, and it was found that the peak period of WBGT is later than usual in 2020, and the occurrences of heatstroke in 2020 is characterized by an increase in the occurrences of heatstroke in people over 65 years old and outdoors, and a decrease in the occurrences of heatstroke in people under 65 years old and indoors. © 2021 IEEE.
Full text:
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Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel
Year:
2021
Document Type:
Article
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