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Paper Abstract and Keywords
Presentation 2023-06-20 14:20
Development and evaluation of a dangerous behavior detection system at station platforms utilizing 3D LiDAR
Yusuke Koyama, Hiroshi Yamamoto (Ritsumeikan Univ.) IA2023-3 ICSS2023-3
Abstract (in Japanese) (See Japanese page) 
(in English) Many accidents occur on railroads although many railroad companies have proposed the measures against the accidents. For example, the companies have installed the platform doors to prevent the accidents, but it requires high cost (about 300 million yen) for each station to prepare the doors in an entire station. On the other hand, it has been clarified that the person who has a possibility to occur the accident (e.g., falling down from the station platform) takes special actions that are predictive of the accident. By specifying the actions in real time, there is a possibility of preventing the accidents. Therefore, in this study, we attempt to develop a new system that observes the behaviors of people on the station platform by analyzing 3D point cloud data taken by 3D LiDAR (Light Detection And Ranging) that can accurately measure the distance, position, and shape of the target object. The proposed system does not have privacy issues because only 3D point cloud data is a target of the analysis. In addition, this system adopts a system design of the edge computing where the sensor nodes not only obtain the point cloud data from the LiDAR but also identifies the behaviors of the people by analyzing the data.
Keyword (in Japanese) (See Japanese page) 
(in English) IoT / railroad accident prevention / 3D LiDAR / 3D point cloud analysis / behavior estimation / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 85, IA2023-3, pp. 13-18, June 2023.
Paper # IA2023-3 
Date of Issue 2023-06-13 (IA, ICSS) 
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)
Download PDF IA2023-3 ICSS2023-3

Conference Information
Committee IA ICSS  
Conference Date 2023-06-20 - 2023-06-21 
Place (in Japanese) (See Japanese page) 
Place (in English) Saga Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Internet Security, etc. 
Paper Information
Registration To IA 
Conference Code 2023-06-IA-ICSS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Development and evaluation of a dangerous behavior detection system at station platforms utilizing 3D LiDAR 
Sub Title (in English)  
Keyword(1) IoT  
Keyword(2) railroad accident prevention  
Keyword(3) 3D LiDAR  
Keyword(4) 3D point cloud analysis  
Keyword(5) behavior estimation  
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1st Author's Name Yusuke Koyama  
1st Author's Affiliation Ritsumeikan University (Ritsumeikan Univ.)
2nd Author's Name Hiroshi Yamamoto  
2nd Author's Affiliation Ritsumeikan University (Ritsumeikan Univ.)
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Speaker Author-1 
Date Time 2023-06-20 14:20:00 
Presentation Time 25 minutes 
Registration for IA 
Paper # IA2023-3, ICSS2023-3 
Volume (vol) vol.123 
Number (no) no.85(IA), no.86(ICSS) 
Page pp.13-18 
#Pages 6 
Date of Issue 2023-06-13 (IA, ICSS) 

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