Machine vision-based urban farming growth monitoring system

Raden Arief Setyawan; Achmad Basuki; Chong Yung Wey

doi:10.1109/EECCIS49483.2020.9263449

Machine vision-based urban farming growth monitoring system

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

Abstract

Precision agriculture integrates information technology and agricultural systems to support efficiency, productivity, and agricultural profitability. This paper presents an approach to the growth of the crops for urban farming using machine vision methods. The approach employs Improved Background Subtraction technique to detect the intruder or unwanted objects, and the Green Channel Otsu filtering to detect the growth rate of the crops. The calculated values are then being sent to a server hosted in the cloud for further analysis. The analytics result summarizes in a reporting dashboard to give insight on the growth of the crops.

Original language	English
Title of host publication	EECCIS 2020 - 2020 10th Electrical Power, Electronics, Communications, Controls, and Informatics Seminar
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	183-187
Number of pages	5
ISBN (Electronic)	9781728171098
DOIs	https://doi.org/10.1109/EECCIS49483.2020.9263449
Publication status	Published - 26 Aug 2020
Event	10th Electrical Power, Electronics, Communications, Controls, and Informatics Seminar, EECCIS 2020 - Malang, Indonesia Duration: 26 Aug 2020 → 28 Aug 2020

Publication series

Name	EECCIS 2020 - 2020 10th Electrical Power, Electronics, Communications, Controls, and Informatics Seminar

Conference

Conference	10th Electrical Power, Electronics, Communications, Controls, and Informatics Seminar, EECCIS 2020
Country/Territory	Indonesia
City	Malang
Period	26/08/20 → 28/08/20

UN SDGs

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

SDG 2 Zero Hunger

Keywords

Component
Formatting
Insert (keywords)
Style
Styling

Access to Document

10.1109/EECCIS49483.2020.9263449

Cite this

Setyawan, R. A., Basuki, A., & Wey, C. Y. (2020). Machine vision-based urban farming growth monitoring system. In EECCIS 2020 - 2020 10th Electrical Power, Electronics, Communications, Controls, and Informatics Seminar (pp. 183-187). Article 9263449 (EECCIS 2020 - 2020 10th Electrical Power, Electronics, Communications, Controls, and Informatics Seminar). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EECCIS49483.2020.9263449

Setyawan, Raden Arief ; Basuki, Achmad ; Wey, Chong Yung. / Machine vision-based urban farming growth monitoring system. EECCIS 2020 - 2020 10th Electrical Power, Electronics, Communications, Controls, and Informatics Seminar. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 183-187 (EECCIS 2020 - 2020 10th Electrical Power, Electronics, Communications, Controls, and Informatics Seminar).

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abstract = "Precision agriculture integrates information technology and agricultural systems to support efficiency, productivity, and agricultural profitability. This paper presents an approach to the growth of the crops for urban farming using machine vision methods. The approach employs Improved Background Subtraction technique to detect the intruder or unwanted objects, and the Green Channel Otsu filtering to detect the growth rate of the crops. The calculated values are then being sent to a server hosted in the cloud for further analysis. The analytics result summarizes in a reporting dashboard to give insight on the growth of the crops.",

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author = "Setyawan, \{Raden Arief\} and Achmad Basuki and Wey, \{Chong Yung\}",

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year = "2020",

month = aug,

day = "26",

doi = "10.1109/EECCIS49483.2020.9263449",

language = "English",

series = "EECCIS 2020 - 2020 10th Electrical Power, Electronics, Communications, Controls, and Informatics Seminar",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Setyawan, RA , Basuki, A & Wey, CY 2020, Machine vision-based urban farming growth monitoring system. in EECCIS 2020 - 2020 10th Electrical Power, Electronics, Communications, Controls, and Informatics Seminar., 9263449, EECCIS 2020 - 2020 10th Electrical Power, Electronics, Communications, Controls, and Informatics Seminar, Institute of Electrical and Electronics Engineers Inc., pp. 183-187, 10th Electrical Power, Electronics, Communications, Controls, and Informatics Seminar, EECCIS 2020, Malang, Indonesia, 26/08/20. https://doi.org/10.1109/EECCIS49483.2020.9263449

Machine vision-based urban farming growth monitoring system. / Setyawan, Raden Arief ; Basuki, Achmad; Wey, Chong Yung.
EECCIS 2020 - 2020 10th Electrical Power, Electronics, Communications, Controls, and Informatics Seminar. Institute of Electrical and Electronics Engineers Inc., 2020. p. 183-187 9263449 (EECCIS 2020 - 2020 10th Electrical Power, Electronics, Communications, Controls, and Informatics Seminar).

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

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AU - Basuki, Achmad

AU - Wey, Chong Yung

PY - 2020/8/26

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N2 - Precision agriculture integrates information technology and agricultural systems to support efficiency, productivity, and agricultural profitability. This paper presents an approach to the growth of the crops for urban farming using machine vision methods. The approach employs Improved Background Subtraction technique to detect the intruder or unwanted objects, and the Green Channel Otsu filtering to detect the growth rate of the crops. The calculated values are then being sent to a server hosted in the cloud for further analysis. The analytics result summarizes in a reporting dashboard to give insight on the growth of the crops.

AB - Precision agriculture integrates information technology and agricultural systems to support efficiency, productivity, and agricultural profitability. This paper presents an approach to the growth of the crops for urban farming using machine vision methods. The approach employs Improved Background Subtraction technique to detect the intruder or unwanted objects, and the Green Channel Otsu filtering to detect the growth rate of the crops. The calculated values are then being sent to a server hosted in the cloud for further analysis. The analytics result summarizes in a reporting dashboard to give insight on the growth of the crops.

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KW - Formatting

KW - Insert (keywords)

KW - Style

KW - Styling

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U2 - 10.1109/EECCIS49483.2020.9263449

DO - 10.1109/EECCIS49483.2020.9263449

M3 - Conference contribution

AN - SCOPUS:85099559547

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BT - EECCIS 2020 - 2020 10th Electrical Power, Electronics, Communications, Controls, and Informatics Seminar

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Setyawan RA , Basuki A, Wey CY. Machine vision-based urban farming growth monitoring system. In EECCIS 2020 - 2020 10th Electrical Power, Electronics, Communications, Controls, and Informatics Seminar. Institute of Electrical and Electronics Engineers Inc. 2020. p. 183-187. 9263449. (EECCIS 2020 - 2020 10th Electrical Power, Electronics, Communications, Controls, and Informatics Seminar). doi: 10.1109/EECCIS49483.2020.9263449

Machine vision-based urban farming growth monitoring system

Abstract

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UN SDGs

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