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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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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)  
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)  
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
Date of Issue 2017-10-12 (SP, WIT) 


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