Presentation 2018-07-11
[Encouragement Talk] Bayesian Optimization for Searching for the Optimal Climate Recipe in Completely Controlled Plant Factory
Tatsuya Iizuka, Ryo Shigeta, Yoshihiro Kawahara,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) A data-driven method for improving the productivity in plant factories is desired. The environmental response including growth speed depends on when and how the surrounding environment is changed. Several studies have applied a machine learning method that could handle time series data such as Recurrent Neural Network to achieve an optimal environment. The key has been to construct the predictor of environmental response given the time series of past environment data as train data. However, few studies have focused on how to collect the train data. An intelligent sampling method can reduce the required size of it and time for the entire experiment. In this paper, we propose a novel sampling method of environmental data points in plant factories to achieve the optimal environment with a small number of data. Bayesian Optimization is applied to maximize the growth rate of leaf area index in our experiment.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Vertical Farming / Bayesian Optimization / Climate Recipe
Paper # ASN2018-24
Date of Issue 2018-07-04 (ASN)

Conference Information
Committee ASN / NS / RCS / SR / RCC
Conference Date 2018/7/11(3days)
Place (in Japanese) (See Japanese page)
Place (in English) Hakodate Arena
Topics (in Japanese) (See Japanese page)
Topics (in English) Wireless Distributed Network, Machine Learning and AI for Wireless Communications and Networks, M2M (Machine-to-Machine), D2D (Device-to-Device), IoT(Internet of Things), etc.
Chair Hiraku Okada(Nagoya Univ.) / Yoshikatsu Okazaki(NTT) / Tomoaki Otsuki(Keio Univ.) / Kenta Umebayashi(Tokyo Univ. of Agric. and Tech.) / Kazunori Hayashi(Osaka City Univ.)
Vice Chair Koji Yamamoto(Kyoto Univ.) / Jin Nakazawa(Keio Univ.) / Kazuya Monden(Hitachi) / Akihiro Nakao(Univ. of Tokyo) / Eisuke Fukuda(Fujitsu Labs.) / Satoshi Suyama(NTT DoCoMo) / Fumiaki Maehara(Waseda Univ.) / Masayuki Ariyoshi(NEC) / Suguru Kameda(Tohoku Univ.) / Shunichi Azuma(Nagoya Univ.) / HUAN-BANG LI(NICT)
Secretary Koji Yamamoto(NICT) / Jin Nakazawa(Sophia Univ.) / Kazuya Monden(Kanagawa Inst. of Tech.) / Akihiro Nakao(NTT) / Eisuke Fukuda(Osaka Pref Univ.) / Satoshi Suyama(Hokkaido Univ.) / Fumiaki Maehara(NTT) / Masayuki Ariyoshi(NICT) / Suguru Kameda(ATR) / Shunichi Azuma(Univ. of Electro-Comm.) / HUAN-BANG LI(Kagawa Univ.)
Assistant Masafumi Hashimoto(Osaka Univ.) / Tomoyuki Ota(Hiroshima City Univ.) / Tatsuya Kikuzuki(Fujitu Lab.) / Ryo Nakano(HITACHI) / Yoshifumi Hotta(Mitsubishi Electric) / Kenichi Kashibuchi(NTT) / Kazushi Muraoka(NTT DOCOMO) / Shinsuke Ibi(Osaka Univ.) / Hiroshi Nishimoto(Mitsubishi Electric) / Koichi Adachi(Univ. of Electro-Comm.) / Osamu Nakamura(Sharp) / Gia Khanh Tran(Tokyo Inst. of Tech.) / Syusuke Narieda(Mie Univ.) / Koji Ohshima(Kozo Keikaku Engineering) / Mai Ohta(Fukuoka Univ.) / Teppei Oyama(Fujitsu Lab.) / Toshinori Kagawa(NICT) / Masateru Ogura(NAIST)

Paper Information
Registration To Technical Committee on Ambient intelligence and Sensor Networks / Technical Committee on Network Systems / Technical Committee on Radio Communication Systems / Technical Committee on Smart Radio / Technical Committee on Reliable Communication and Control
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) [Encouragement Talk] Bayesian Optimization for Searching for the Optimal Climate Recipe in Completely Controlled Plant Factory
Sub Title (in English)
Keyword(1) Vertical Farming
Keyword(2) Bayesian Optimization
Keyword(3) Climate Recipe
1st Author's Name Tatsuya Iizuka
1st Author's Affiliation The University of Tokyo(Tokyo Univ.)
2nd Author's Name Ryo Shigeta
2nd Author's Affiliation The University of Tokyo(Tokyo Univ.)
3rd Author's Name Yoshihiro Kawahara
3rd Author's Affiliation The University of Tokyo(Tokyo Univ.)
Date 2018-07-11
Paper # ASN2018-24
Volume (vol) vol.118
Number (no) ASN-127
Page pp.pp.47-52(ASN),
#Pages 6
Date of Issue 2018-07-04 (ASN)