| Paper Abstract and Keywords |
| Presentation |
2026-05-14 09:15
Reservoir Computing-based Wi-Fi CSI for People Counting Hinaki Sugiura, Yusuke Fukazawa, Masakatsu Ogawa (Sophia Univ) SeMI2026-1 |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
In recent years, crowd monitoring and pedestrian counting in railway stations and public spaces have become increasingly important for safety management and facility operations. While conventional camera-based approaches are highly effective, they raise concerns regarding privacy protection and installation costs. This study proposes a method for estimating the number of pedestrians within a short time interval by utilizing Channel State Information (CSI) obtained from publicly deployed wireless LAN beacons, without relying on cameras. As the machine learning model, we employ Reservoir Computing (RC), which is well suited for time-series data processing. RC requires relatively low computational cost for training and enables real-time processing, making it highly compatible with edge computing environments. In this study, we aim to realize lightweight edge AI by introducing RC into Integrated Sensing and Communication (ISAC). We developed an RC-based model and compared its performance with RNN, LSTM, and CNN models. Experimental results demonstrate that the RC model achieves both fast training and highly accurate pedestrian count estimation. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
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| Reference Info. |
IEICE Tech. Rep., vol. 126, no. 15, SeMI2026-1, pp. 1-6, May 2026. |
| Paper # |
SeMI2026-1 |
| Date of Issue |
2026-05-07 (SeMI) |
| 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 |
SeMI2026-1 |
| Conference Information |
| Committee |
SeMI IPSJ-MBL IPSJ-ITS IPSJ-DPS |
| Conference Date |
2026-05-13 - 2026-05-15 |
| Place (in Japanese) |
(See Japanese page) |
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(See Japanese page) |
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| Paper Information |
| Registration To |
SeMI |
| Conference Code |
2026-05-SeMI-MBL-ITS-DPS |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Reservoir Computing-based Wi-Fi CSI for People Counting |
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| 1st Author's Name |
Hinaki Sugiura |
| 1st Author's Affiliation |
Sophia University (Sophia Univ) |
| 2nd Author's Name |
Yusuke Fukazawa |
| 2nd Author's Affiliation |
Sophia University (Sophia Univ) |
| 3rd Author's Name |
Masakatsu Ogawa |
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Sophia University (Sophia Univ) |
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| Speaker |
Author-1 |
| Date Time |
2026-05-14 09:15:00 |
| Presentation Time |
25 minutes |
| Registration for |
SeMI |
| Paper # |
SeMI2026-1 |
| Volume (vol) |
vol.126 |
| Number (no) |
no.15 |
| Page |
pp.1-6 |
| #Pages |
6 |
| Date of Issue |
2026-05-07 (SeMI) |