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| Paper Abstract and Keywords | ||
| Presentation | 2022-03-12 10:00 A Method and Evaluation of Train Congestion Estimation Using BLE Signals Eigo Taya, Yuji Kanamitsu, Koki Tachibana (NAIST), Yugo Nakamura (QU), Matsuda Yuki (NAIST/RIKEN/JST PRESTO), Suwa Hirohiko, Keiichi Yasumoto (NAIST/RIKEN)  AI2021-30 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Trains play an essential role in transportation in supporting people's lives. In recent years, it has become necessary to estimate the degree of congestion in each train vehicle to prevent the pandemic of COVID-19 and improve passengers' comfort. However, it is difficult to estimate the degree of congestion without violating passengers' privacy. We have developed and evaluated a system to estimate the degree of bus congestion while protecting passengers' privacy by using BLE signals. This paper used the above system to collect BLE signals on a train cooperating with Kintetsu Railway Co., Ltd. The congestion of each train vehicle is then estimated using a machine learning regression model. The results show that the MAE and MAPE can be estimated with an accuracy of 0.56 and 0.27, respectively. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | BLE / Train / Public transportation / Congestion estimation / Machine learning / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 121, no. 439, AI2021-30, pp. 25-30, March 2022. | |
| Paper # | AI2021-30 | |
| Date of Issue | 2022-03-05 (AI) | |
| 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 | AI2021-30 |
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| Conference Information | |
| Committee | AI JSAI-SAI JSAI-KBS JSAI-DOCMAS IPSJ-ICS |
| Conference Date | 2022-03-12 - 2022-03-12 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | WSSIT2022 |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Social System and Information Technology |
| Paper Information | |
| Registration To | AI |
| Conference Code | 2022-03-AI-SAI-KBS-DOCMAS-ICS |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A Method and Evaluation of Train Congestion Estimation Using BLE Signals |
| Sub Title (in English) | |
| Keyword(1) | BLE |
| Keyword(2) | Train |
| Keyword(3) | Public transportation |
| Keyword(4) | Congestion estimation |
| Keyword(5) | Machine learning |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Eigo Taya |
| 1st Author's Affiliation | Nara Institute of Science and Technology/RIKEN Center (NAIST) |
| 2nd Author's Name | Yuji Kanamitsu |
| 2nd Author's Affiliation | Nara Institute of Science and Technology/RIKEN Center (NAIST) |
| 3rd Author's Name | Koki Tachibana |
| 3rd Author's Affiliation | Nara Institute of Science and Technology (NAIST) |
| 4th Author's Name | Yugo Nakamura |
| 4th Author's Affiliation | Kyushu University (QU) |
| 5th Author's Name | Matsuda Yuki |
| 5th Author's Affiliation | Nara Institute of Science and Technology/RIKEN Center/Japan Science and Technology Agency (NAIST/RIKEN/JST PRESTO) |
| 6th Author's Name | Suwa Hirohiko |
| 6th Author's Affiliation | Nara Institute of Science and Technology/RIKEN Center (NAIST/RIKEN) |
| 7th Author's Name | Keiichi Yasumoto |
| 7th Author's Affiliation | Nara Institute of Science and Technology/RIKEN Center (NAIST/RIKEN) |
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| Speaker | Author-1 |
| Date Time | 2022-03-12 10:00:00 |
| Presentation Time | 15 minutes |
| Registration for | AI |
| Paper # | AI2021-30 |
| Volume (vol) | vol.121 |
| Number (no) | no.439 |
| Page | pp.25-30 |
| #Pages | 6 |
| Date of Issue | 2022-03-05 (AI) |
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