Paper Abstract and Keywords |
Presentation |
2017-10-20 11:30
Machine Learning Approach to Recognizing Indoor Activities based on Environment Sensing and Activity Logs on Changing Points Kazunari Tamamizu, Seiji Sakakibara, Sachio Saiki, Masahide Nakamura (Kobe Univ.), Kiyoshi Yasuda (Chiba Rosai Hospital) SP2017-52 WIT2017-48 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
The ICT-based elderly monitoring systems attract great attention as a promising technology for home elderly care. However, the conventional systems have limitations of deployment cost and invasiveness, effort of activity labeling, and a lack of communication. To cope with the limitations, we proposed the new system that captures activities of the elderly. Specificallly, in this paper, we focus on Auto Recognition in Activity Recognition Service that composes the proposed system and implement Auto Recognition. Also, we collect sensor data and activity logs and execute machine learning to evaluate Auto Recognition accuracy. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
elderly care / home care / machine learning / activity recognition / change point detection / / / |
Reference Info. |
IEICE Tech. Rep., vol. 117, no. 251, WIT2017-48, pp. 101-106, Oct. 2017. |
Paper # |
WIT2017-48 |
Date of Issue |
2017-10-12 (SP, WIT) |
ISSN |
Print edition: ISSN 0913-5685 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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SP2017-52 WIT2017-48 |
Conference Information |
Committee |
WIT SP |
Conference Date |
2017-10-19 - 2017-10-20 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Tobata Library of Kyutech (Kitakyushu) |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
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Paper Information |
Registration To |
WIT |
Conference Code |
2017-10-WIT-SP |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Machine Learning Approach to Recognizing Indoor Activities based on Environment Sensing and Activity Logs on Changing Points |
Sub Title (in English) |
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Keyword(1) |
elderly care |
Keyword(2) |
home care |
Keyword(3) |
machine learning |
Keyword(4) |
activity recognition |
Keyword(5) |
change point detection |
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1st Author's Name |
Kazunari Tamamizu |
1st Author's Affiliation |
Kobe University (Kobe Univ.) |
2nd Author's Name |
Seiji Sakakibara |
2nd Author's Affiliation |
Kobe University (Kobe Univ.) |
3rd Author's Name |
Sachio Saiki |
3rd Author's Affiliation |
Kobe University (Kobe Univ.) |
4th Author's Name |
Masahide Nakamura |
4th Author's Affiliation |
Kobe University (Kobe Univ.) |
5th Author's Name |
Kiyoshi Yasuda |
5th Author's Affiliation |
Chiba Rosai Hospital (Chiba Rosai Hospital) |
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Speaker |
Author-1 |
Date Time |
2017-10-20 11:30:00 |
Presentation Time |
20 minutes |
Registration for |
WIT |
Paper # |
SP2017-52, WIT2017-48 |
Volume (vol) |
vol.117 |
Number (no) |
no.250(SP), no.251(WIT) |
Page |
pp.101-106 |
#Pages |
6 |
Date of Issue |
2017-10-12 (SP, WIT) |
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