Paper Abstract and Keywords |
Presentation |
2020-11-13 11:05
Analyzing and Predicting Ambulance Demand for Heat Stroke Using Fine-grained Dispatch Log Tetsuya Nakai, Sachio Saiki, Masahide Nakamura (Kobe Univ.) KBSE2020-11 SC2020-15 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In recent years, the number of emergency transports is on the increase
The number is expected to continue to grow.
As a result, emergency medical service will be busier.
Therefore, emergency medical service needs taking more appropriate and concrete measures by analyzing dispatch logs.
In this paper, we focus on summer heat stroke as a contributing factor to the busyness on the emergency medical service.
In order to identify whether the number of heat stroke transports affects the busyness of emergency medical service, we analyze from the rush time.
Moreover, we predict the number of persons transported for heat stroke per day.
By analyzing in detail the dispatch logs of the Kobe Fire Department, we found that heat stroke affects the busyness of emergency medical service.
In addition, we were able to predict the number of persons transported for heat stroke from weather data. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
heat stroke / ambulance / smartcity / demand prediction / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 120, no. 232, SC2020-15, pp. 13-19, Nov. 2020. |
Paper # |
SC2020-15 |
Date of Issue |
2020-11-06 (KBSE, SC) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
Notes on Review |
This article is a technical report without peer review, and its polished version will be published elsewhere. |
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KBSE2020-11 SC2020-15 |
Conference Information |
Committee |
KBSE SC |
Conference Date |
2020-11-13 - 2020-11-14 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Online + Kikai-Shinko-Kaikan Bldg. |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
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Paper Information |
Registration To |
SC |
Conference Code |
2020-11-KBSE-SC |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Analyzing and Predicting Ambulance Demand for Heat Stroke Using Fine-grained Dispatch Log |
Sub Title (in English) |
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Keyword(1) |
heat stroke |
Keyword(2) |
ambulance |
Keyword(3) |
smartcity |
Keyword(4) |
demand prediction |
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1st Author's Name |
Tetsuya Nakai |
1st Author's Affiliation |
Kobe University (Kobe Univ.) |
2nd Author's Name |
Sachio Saiki |
2nd Author's Affiliation |
Kobe University (Kobe Univ.) |
3rd Author's Name |
Masahide Nakamura |
3rd Author's Affiliation |
Kobe University (Kobe Univ.) |
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Speaker |
Author-1 |
Date Time |
2020-11-13 11:05:00 |
Presentation Time |
30 minutes |
Registration for |
SC |
Paper # |
KBSE2020-11, SC2020-15 |
Volume (vol) |
vol.120 |
Number (no) |
no.231(KBSE), no.232(SC) |
Page |
pp.13-19 |
#Pages |
7 |
Date of Issue |
2020-11-06 (KBSE, SC) |
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