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 | |
| 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 |
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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
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
}
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.
ER -