Presentation 2016-03-04
A Study on Location Estimation Method by Wi-SUN Using Machine Learning
Hiroshi Sakamoto, Hiroyuki Yasuda, Thong Huynh, Kaori Kuroda, Yozo Shoji, Mikio Hasegawa,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Wi-SUN is a wireless communication standard that has been developed as communication scheme for smart meter to record information of domestic consumption, such as electric energy, gas and water. In this paper, we study about the power-saving location detection system for wireless devices using the received signal strength indication (RSSI) of Wi-SUN. Since the RSSI between wireless devices is changed by the distance and the environments, in this paper, we apply machine learning algorithm for improving the accuracy of the position estimation. We use Support Vector Regression as a machine learning algorithm, and evaluate the performance of the proposed method by experiments in real environment using the Wi-SUN devices. We compare the proposed method with the conventional method, and show that it can significantly reduce the error by the proposed method.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Wi-SUN / Location estimation / Received signal strength indication / Support Vector Machines / Machine learning
Paper # CCS2015-78
Date of Issue 2016-02-25 (CCS)

Conference Information
Committee RCS / CCS / SR / SRW
Conference Date 2016/3/2(3days)
Place (in Japanese) (See Japanese page)
Place (in English) Tokyo Institute of Technology
Topics (in Japanese) (See Japanese page)
Topics (in English) Mobile Communication Workshop
Chair Makoto Taromaru(Fukuoka Univ.) / Hiroo Sekiya(Chiba Univ.) / Takeo Fujii(Univ. of Electro-Comm.) / Hiroshi Harada(Kyoto Univ.)
Vice Chair Hidekazu Murata(Kyoto Univ.) / Satoshi Denno(Okayama Univ.) / Yukitoshi Sanada(Keio Univ.) / Yasuhiro Tsubo(Ritsumeikan Univ.) / Naoki Wakamiya(Osaka Univ.) / Kenta Umebayashi(Tokyo Univ. of Agric. and Tech.) / Masayuki Ariyoshi(NEC) / Masafumi Kato(Fujitsu) / Satoshi Denno(Okayama Univ.)
Secretary Hidekazu Murata(Mitsubishi Electric) / Satoshi Denno(NTT DoCoMo) / Yukitoshi Sanada(Kagawa National College of Tech.) / Yasuhiro Tsubo(Kyoto Sangyo Univ.) / Naoki Wakamiya(Shinshu Univ.) / Kenta Umebayashi(NICT) / Masayuki Ariyoshi(NTT) / Masafumi Kato(NICT) / Satoshi Denno
Assistant Jun Mashino(NTT) / Tetsuya Yamamoto(Panasonic) / Takamichi Inoue(NEC) / Tomoya Tandai(Toshiba) / Toshihiko Nishimura(Hokkaido Univ.) / Takayuki Kimura(Nippon Inst. of Tech.) / Song-Ju Kim(NIMS) / Ryo Takahashi(Kyoto Univ.) / Junnosuke Teramae(Osaka Univ.) / Kazuto Yano(ATR) / Mamiko Inamori(Tokai Univ.) / Hiroyuki Shiba(NTT) / Gia Khanh Tran(Tokyo Inst. of Tech.) / Wen Yun(Fujitsu) / Keiichi Mizutani(Kyoto Univ.)

Paper Information
Registration To Technical Committee on Radio Communication Systems / Technical Committee on Complex Communication Sciences / Technical Committee on Smart Radio / Technical Committee on Short Range Wireless Communications
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Study on Location Estimation Method by Wi-SUN Using Machine Learning
Sub Title (in English)
Keyword(1) Wi-SUN
Keyword(2) Location estimation
Keyword(3) Received signal strength indication
Keyword(4) Support Vector Machines
Keyword(5) Machine learning
1st Author's Name Hiroshi Sakamoto
1st Author's Affiliation Tokyo University of Science(Tokyo Univ. of Science)
2nd Author's Name Hiroyuki Yasuda
2nd Author's Affiliation Tokyo University of Science(Tokyo Univ. of Science)
3rd Author's Name Thong Huynh
3rd Author's Affiliation Tokyo University of Science(Tokyo Univ. of Science)
4th Author's Name Kaori Kuroda
4th Author's Affiliation Tokyo University of Science(Tokyo Univ. of Science)
5th Author's Name Yozo Shoji
5th Author's Affiliation National Institute of Information and Communications Technology(NICT)
6th Author's Name Mikio Hasegawa
6th Author's Affiliation Tokyo University of Science(Tokyo Univ. of Science)
Date 2016-03-04
Paper # CCS2015-78
Volume (vol) vol.115
Number (no) CCS-475
Page pp.pp.63-66(CCS),
#Pages 4
Date of Issue 2016-02-25 (CCS)