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Paper Abstract and Keywords
Presentation 2018-01-19 15:45
Evaluation of Methods for Detecting Change of Indoor Walking Patterns Using Sparse Position Information
Kazuki Takagi, Ryoichi Shinkuma (Kyoto Univ.), Hideyuki shimizu, Hisashi Sakamoto (NEC Solution Innovators) MoNA2017-59
Abstract (in Japanese) (See Japanese page) 
(in English) Recently, the Internet-of-Things (IoT) technology has been attracting a lot of attention as a solution that detects health risk.Using cameras or wearable devices is a typical approach to track people’s behaviors in their house.However,these devices have drawbacks: people feel uncomfortable from the privacy aspect if they are always watched by cameras; people feel annoyed if they are required to always carry wearable devices.Therefore, vibration sensors or human sensors could be more appropriate for behavior monitoring in a indoor private environment like houses though they might be able to collect discrete and sparse data.The authors previously proposed a method that detects changes in behavior patterns of elderly people who live alone by using sparse position information from sensors.Our method successfully models usual behavior patters by representing movement patterns between multiple sensors of people as a network graph.Then, our method detects changes in people’s behaviors by scoring the similarity of network graphs between the measured behavior pattern and the usual behavior patters. This report shows how the performance of detection by our method varies with the density f placement of sensors.
Keyword (in Japanese) (See Japanese page) 
(in English) Anomaly Detection / Elderly Care / Position Tracking / Network Graph / / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 390, MoNA2017-59, pp. 99-102, Jan. 2018.
Paper # MoNA2017-59 
Date of Issue 2018-01-11 (MoNA) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
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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)
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Conference Information
Committee MoNA  
Conference Date 2018-01-18 - 2018-01-19 
Place (in Japanese) (See Japanese page) 
Place (in English) Campus Plaza Kyoto 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Mobile Network, Application of Machine Learning, Mobile Data, etc. 
Paper Information
Registration To MoNA 
Conference Code 2018-01-MoNA 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Evaluation of Methods for Detecting Change of Indoor Walking Patterns Using Sparse Position Information 
Sub Title (in English)  
Keyword(1) Anomaly Detection  
Keyword(2) Elderly Care  
Keyword(3) Position Tracking  
Keyword(4) Network Graph  
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1st Author's Name Kazuki Takagi  
1st Author's Affiliation Kyoto University (Kyoto Univ.)
2nd Author's Name Ryoichi Shinkuma  
2nd Author's Affiliation Kyoto University (Kyoto Univ.)
3rd Author's Name Hideyuki shimizu  
3rd Author's Affiliation NEC Solution Innovators, Ltd. (NEC Solution Innovators)
4th Author's Name Hisashi Sakamoto  
4th Author's Affiliation NEC Solution Innovators, Ltd. (NEC Solution Innovators)
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Speaker Author-1 
Date Time 2018-01-19 15:45:00 
Presentation Time 25 minutes 
Registration for MoNA 
Paper # MoNA2017-59 
Volume (vol) vol.117 
Number (no) no.390 
Page pp.99-102 
#Pages
Date of Issue 2018-01-11 (MoNA) 


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