Internet of Things for Greenhouse Monitoring System Using Deep Learning and Bot Notification Services

Nuttakarn Kitpo; Yosuke Kugai; Masahiro Inoue; Taketoshi Yokemura; Shinichi Satomura

doi:10.1109/ICCE.2019.8661999

Internet of Things for Greenhouse Monitoring System Using Deep Learning and Bot Notification Services

Nuttakarn Kitpo, Yosuke Kugai, Masahiro Inoue, Taketoshi Yokemura, Shinichi Satomura

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

2 Citations (Scopus)

Abstract

Internet of things (IoT) plays a big important role in agricultural industry recently in order to provide a support to farmers such as growth monitoring system of temperature, humidity and water supply, and also early disease monitoring and detection system. To provide a smart farming solutions, this paper proposed an IoT system with a bot notification on tomato growing stages. The tomato dataset was obtained from Shinchi Agri-Green, the tomato greenhouse in Fukushima, Japan. We trained and tested the deep learning model to detect the fruit proposal region. Then, the detected regions were classified into 6 stages of fruit growth using the visible wavelength as a feature in SVM classification with the weight accuracy of 91.5%.

Original language	English
Title of host publication	2019 IEEE International Conference on Consumer Electronics, ICCE 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538679104
DOIs	https://doi.org/10.1109/ICCE.2019.8661999
Publication status	Published - 2019 Mar 6
Event	2019 IEEE International Conference on Consumer Electronics, ICCE 2019 - Las Vegas, United States Duration: 2019 Jan 11 → 2019 Jan 13

Publication series

Name	2019 IEEE International Conference on Consumer Electronics, ICCE 2019

Conference

Conference	2019 IEEE International Conference on Consumer Electronics, ICCE 2019
Country	United States
City	Las Vegas
Period	19/1/11 → 19/1/13

Fingerprint

Keywords

bot notification
deep learning
greenhouse
image processing
internet of things
tomato growth

ASJC Scopus subject areas

Industrial and Manufacturing Engineering
Media Technology
Electrical and Electronic Engineering

Cite this

Kitpo, N., Kugai, Y., Inoue, M., Yokemura, T., & Satomura, S. (2019). Internet of Things for Greenhouse Monitoring System Using Deep Learning and Bot Notification Services. In 2019 IEEE International Conference on Consumer Electronics, ICCE 2019 [8661999] (2019 IEEE International Conference on Consumer Electronics, ICCE 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCE.2019.8661999

Internet of Things for Greenhouse Monitoring System Using Deep Learning and Bot Notification Services. / Kitpo, Nuttakarn; Kugai, Yosuke; Inoue, Masahiro ; Yokemura, Taketoshi; Satomura, Shinichi.

2019 IEEE International Conference on Consumer Electronics, ICCE 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8661999 (2019 IEEE International Conference on Consumer Electronics, ICCE 2019).

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

Kitpo, N, Kugai, Y, Inoue, M , Yokemura, T & Satomura, S 2019, Internet of Things for Greenhouse Monitoring System Using Deep Learning and Bot Notification Services. in 2019 IEEE International Conference on Consumer Electronics, ICCE 2019., 8661999, 2019 IEEE International Conference on Consumer Electronics, ICCE 2019, Institute of Electrical and Electronics Engineers Inc., 2019 IEEE International Conference on Consumer Electronics, ICCE 2019, Las Vegas, United States, 19/1/11. https://doi.org/10.1109/ICCE.2019.8661999

Kitpo N, Kugai Y, Inoue M , Yokemura T, Satomura S. Internet of Things for Greenhouse Monitoring System Using Deep Learning and Bot Notification Services. In 2019 IEEE International Conference on Consumer Electronics, ICCE 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 8661999. (2019 IEEE International Conference on Consumer Electronics, ICCE 2019). https://doi.org/10.1109/ICCE.2019.8661999

Kitpo, Nuttakarn ; Kugai, Yosuke ; Inoue, Masahiro ; Yokemura, Taketoshi ; Satomura, Shinichi. / Internet of Things for Greenhouse Monitoring System Using Deep Learning and Bot Notification Services. 2019 IEEE International Conference on Consumer Electronics, ICCE 2019. Institute of Electrical and Electronics Engineers Inc., 2019. (2019 IEEE International Conference on Consumer Electronics, ICCE 2019).

@inproceedings{0f7e9b623d94400fb9e62303f0df5176,

title = "Internet of Things for Greenhouse Monitoring System Using Deep Learning and Bot Notification Services",

abstract = "Internet of things (IoT) plays a big important role in agricultural industry recently in order to provide a support to farmers such as growth monitoring system of temperature, humidity and water supply, and also early disease monitoring and detection system. To provide a smart farming solutions, this paper proposed an IoT system with a bot notification on tomato growing stages. The tomato dataset was obtained from Shinchi Agri-Green, the tomato greenhouse in Fukushima, Japan. We trained and tested the deep learning model to detect the fruit proposal region. Then, the detected regions were classified into 6 stages of fruit growth using the visible wavelength as a feature in SVM classification with the weight accuracy of 91.5{\%}.",

keywords = "bot notification, deep learning, greenhouse, image processing, internet of things, tomato growth",

author = "Nuttakarn Kitpo and Yosuke Kugai and Masahiro Inoue and Taketoshi Yokemura and Shinichi Satomura",

year = "2019",

month = "3",

day = "6",

doi = "10.1109/ICCE.2019.8661999",

language = "English",

series = "2019 IEEE International Conference on Consumer Electronics, ICCE 2019",

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

booktitle = "2019 IEEE International Conference on Consumer Electronics, ICCE 2019",

address = "United States",

note = "2019 IEEE International Conference on Consumer Electronics, ICCE 2019 ; Conference date: 11-01-2019 Through 13-01-2019",

}

TY - GEN

T1 - Internet of Things for Greenhouse Monitoring System Using Deep Learning and Bot Notification Services

AU - Kitpo, Nuttakarn

AU - Kugai, Yosuke

AU - Inoue, Masahiro

AU - Yokemura, Taketoshi

AU - Satomura, Shinichi

PY - 2019/3/6

Y1 - 2019/3/6

N2 - Internet of things (IoT) plays a big important role in agricultural industry recently in order to provide a support to farmers such as growth monitoring system of temperature, humidity and water supply, and also early disease monitoring and detection system. To provide a smart farming solutions, this paper proposed an IoT system with a bot notification on tomato growing stages. The tomato dataset was obtained from Shinchi Agri-Green, the tomato greenhouse in Fukushima, Japan. We trained and tested the deep learning model to detect the fruit proposal region. Then, the detected regions were classified into 6 stages of fruit growth using the visible wavelength as a feature in SVM classification with the weight accuracy of 91.5%.

AB - Internet of things (IoT) plays a big important role in agricultural industry recently in order to provide a support to farmers such as growth monitoring system of temperature, humidity and water supply, and also early disease monitoring and detection system. To provide a smart farming solutions, this paper proposed an IoT system with a bot notification on tomato growing stages. The tomato dataset was obtained from Shinchi Agri-Green, the tomato greenhouse in Fukushima, Japan. We trained and tested the deep learning model to detect the fruit proposal region. Then, the detected regions were classified into 6 stages of fruit growth using the visible wavelength as a feature in SVM classification with the weight accuracy of 91.5%.

KW - bot notification

KW - deep learning

KW - greenhouse

KW - image processing

KW - internet of things

KW - tomato growth

UR - http://www.scopus.com/inward/record.url?scp=85063811910&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85063811910&partnerID=8YFLogxK

U2 - 10.1109/ICCE.2019.8661999

DO - 10.1109/ICCE.2019.8661999

M3 - Conference contribution

AN - SCOPUS:85063811910

T3 - 2019 IEEE International Conference on Consumer Electronics, ICCE 2019

BT - 2019 IEEE International Conference on Consumer Electronics, ICCE 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2019 IEEE International Conference on Consumer Electronics, ICCE 2019

Y2 - 11 January 2019 through 13 January 2019

ER -

Access to Document

10.1109/ICCE.2019.8661999