利用应急大数据分析2020年中暑患者

2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD) Pub Date : 2021-11-24 DOI:10.1109/SNPD51163.2021.9705007

Kento Matsuba, S. Saiki, Masahide Nakamura

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引用次数: 0

摘要

本研究利用神户市应急运输大数据对中暑病例进行多方面分析，发现2020年神户市中暑事件与往年不同的特点。分析结果发现，2020年WBGT的高峰期比平时晚，2020年WBGT的高峰期比平时晚，2020年中暑发生的特点是65岁以上人群和室外中暑发生增加，65岁以下人群和室内中暑发生减少。

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Analyzing heatstroke patients in 2020 using Emergency Big Data

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.

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来源期刊

2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)

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