Applications of intelligent machine vision in plant factory

Yusuf Hendrawan; Dimas Firmanda Al Riza; Haruhiko Murase

doi:10.3182/20140824-6-za-1003.01099

Applications of intelligent machine vision in plant factory

Faculty of Agricultural Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

12 Citations (Scopus)

Abstract

Intelligent machine vision has been widely used in plant factory for many purposes. There are two aims in this study i.e. the first is improving the performance of intelligent machine vision for precision irrigation system using optimized feature selection technique and the second is developing intelligent machine vision for precision artificial lighting system using Light Emitting Diode (LED). The proposed feature selection technique used in the first aim is Neural-Discrete Hungry Roach Infestation Optimization (N-DHRIO) algorithm. The intelligent machine vision for precision irrigation system and the precision LED lighting system have successfully been developed, and it shows effective to control moisture content and light intensity of the plant precisely. In large scale plant factory, those systems can optimize plant growth and reduce the water consumption and energy costs.

Original language	English
Title of host publication	19th IFAC World Congress IFAC 2014, Proceedings
Editors	Edward Boje, Xiaohua Xia
Publisher	IFAC Secretariat
Pages	8122-8127
Number of pages	6
ISBN (Electronic)	9783902823625
DOIs	https://doi.org/10.3182/20140824-6-za-1003.01099
Publication status	Published - 2014
Event	19th IFAC World Congress on International Federation of Automatic Control, IFAC 2014 - Cape Town, South Africa Duration: 24 Aug 2014 → 29 Aug 2014

Publication series

Name	IFAC Proceedings Volumes (IFAC-PapersOnline)
Volume	19
ISSN (Print)	1474-6670

Conference

Conference	19th IFAC World Congress on International Federation of Automatic Control, IFAC 2014
Country/Territory	South Africa
City	Cape Town
Period	24/08/14 → 29/08/14

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 2 Zero Hunger
SDG 6 Clean Water and Sanitation

Keywords

Artificial neural network
Image analysis
Pattern recognition
Plant factories

Access to Document

10.3182/20140824-6-za-1003.01099

Cite this

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title = "Applications of intelligent machine vision in plant factory",

abstract = "Intelligent machine vision has been widely used in plant factory for many purposes. There are two aims in this study i.e. the first is improving the performance of intelligent machine vision for precision irrigation system using optimized feature selection technique and the second is developing intelligent machine vision for precision artificial lighting system using Light Emitting Diode (LED). The proposed feature selection technique used in the first aim is Neural-Discrete Hungry Roach Infestation Optimization (N-DHRIO) algorithm. The intelligent machine vision for precision irrigation system and the precision LED lighting system have successfully been developed, and it shows effective to control moisture content and light intensity of the plant precisely. In large scale plant factory, those systems can optimize plant growth and reduce the water consumption and energy costs.",

keywords = "Artificial neural network, Image analysis, Pattern recognition, Plant factories",

author = "Yusuf Hendrawan and \{Al Riza\}, \{Dimas Firmanda\} and Haruhiko Murase",

note = "Publisher Copyright: {\textcopyright} IFAC.; 19th IFAC World Congress on International Federation of Automatic Control, IFAC 2014 ; Conference date: 24-08-2014 Through 29-08-2014",

year = "2014",

doi = "10.3182/20140824-6-za-1003.01099",

language = "English",

series = "IFAC Proceedings Volumes (IFAC-PapersOnline)",

publisher = "IFAC Secretariat",

pages = "8122--8127",

editor = "Edward Boje and Xiaohua Xia",

booktitle = "19th IFAC World Congress IFAC 2014, Proceedings",

}

Hendrawan, Y , Al Riza, DF & Murase, H 2014, Applications of intelligent machine vision in plant factory. in E Boje & X Xia (eds), 19th IFAC World Congress IFAC 2014, Proceedings. IFAC Proceedings Volumes (IFAC-PapersOnline), vol. 19, IFAC Secretariat, pp. 8122-8127, 19th IFAC World Congress on International Federation of Automatic Control, IFAC 2014, Cape Town, South Africa, 24/08/14. https://doi.org/10.3182/20140824-6-za-1003.01099

Applications of intelligent machine vision in plant factory. / Hendrawan, Yusuf ; Al Riza, Dimas Firmanda; Murase, Haruhiko.
19th IFAC World Congress IFAC 2014, Proceedings. ed. / Edward Boje; Xiaohua Xia. IFAC Secretariat, 2014. p. 8122-8127 (IFAC Proceedings Volumes (IFAC-PapersOnline); Vol. 19).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Applications of intelligent machine vision in plant factory

AU - Hendrawan, Yusuf

AU - Al Riza, Dimas Firmanda

AU - Murase, Haruhiko

N1 - Publisher Copyright: © IFAC.

PY - 2014

Y1 - 2014

N2 - Intelligent machine vision has been widely used in plant factory for many purposes. There are two aims in this study i.e. the first is improving the performance of intelligent machine vision for precision irrigation system using optimized feature selection technique and the second is developing intelligent machine vision for precision artificial lighting system using Light Emitting Diode (LED). The proposed feature selection technique used in the first aim is Neural-Discrete Hungry Roach Infestation Optimization (N-DHRIO) algorithm. The intelligent machine vision for precision irrigation system and the precision LED lighting system have successfully been developed, and it shows effective to control moisture content and light intensity of the plant precisely. In large scale plant factory, those systems can optimize plant growth and reduce the water consumption and energy costs.

AB - Intelligent machine vision has been widely used in plant factory for many purposes. There are two aims in this study i.e. the first is improving the performance of intelligent machine vision for precision irrigation system using optimized feature selection technique and the second is developing intelligent machine vision for precision artificial lighting system using Light Emitting Diode (LED). The proposed feature selection technique used in the first aim is Neural-Discrete Hungry Roach Infestation Optimization (N-DHRIO) algorithm. The intelligent machine vision for precision irrigation system and the precision LED lighting system have successfully been developed, and it shows effective to control moisture content and light intensity of the plant precisely. In large scale plant factory, those systems can optimize plant growth and reduce the water consumption and energy costs.

KW - Artificial neural network

KW - Image analysis

KW - Pattern recognition

KW - Plant factories

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DO - 10.3182/20140824-6-za-1003.01099

M3 - Conference contribution

AN - SCOPUS:84929791520

T3 - IFAC Proceedings Volumes (IFAC-PapersOnline)

SP - 8122

EP - 8127

BT - 19th IFAC World Congress IFAC 2014, Proceedings

A2 - Boje, Edward

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PB - IFAC Secretariat

T2 - 19th IFAC World Congress on International Federation of Automatic Control, IFAC 2014

Y2 - 24 August 2014 through 29 August 2014

ER -

Applications of intelligent machine vision in plant factory

Abstract

Publication series

Conference

UN SDGs

Keywords

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