Presentation 2017-11-17
Examination of Methods for Detecting Change of Indoor Walking Patterns Using Sparse Position Information
Kazuki Takagi, Ryoichi Shinkuma, Hideyuki Shimizu, Hisashi Sakamoto,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Recently, the Internet-of-Things (IoT) technology has been attracting a lot of attention as a solution that detects health risk of elderly people by monitoring and analyzing their daily behaviors. 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. In this report, we propose 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 paper validates our method through simulation evaluation.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Anomaly Detection / Elderly Care / Position Tracking / Network Graph
Paper # MoNA2017-20
Date of Issue 2017-11-09 (MoNA)

Conference Information
Committee CNR / IN / MoNA
Conference Date 2017/11/16(2days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Tetsuo Ono(Hokkaido Univ.) / Katsunori Yamaoka(Tokyo Inst. of Tech.) / Ryoichi Shinkuma(Kyoto Univ.)
Vice Chair Masayuki Kanbara(NAIST) / Kazunori Takashio(Keio Univ.) / Takuji Kishida(NTT) / Shigeaki Tagashira(Kansai Univ.) / Gen Kitagata(Tohoku Univ.)
Secretary Masayuki Kanbara(Hokkaido Univ.) / Kazunori Takashio(Panasonic) / Takuji Kishida(NTT) / Shigeaki Tagashira(NTT) / Gen Kitagata(KDDI Research)
Assistant Wataru Mito(SECOM) / Daisuke Yamamoto(Toshiba) / Yoichi Takashima(NTT) / / Koichi Nihei(NEC) / Takayuki Nishio(Kyoto Univ.) / Takato Saito(NTT)

Paper Information
Registration To Technical Committee on Cloud Network Robotics / Technical Committee on Information Networks / Technical Committee on Mobile Network and Applications
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Examination 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
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)
Date 2017-11-17
Paper # MoNA2017-20
Volume (vol) vol.117
Number (no) MoNA-308
Page pp.pp.31-34(MoNA),
#Pages 4
Date of Issue 2017-11-09 (MoNA)