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
N1 - Funding Information:
supported by JSPS KAKENHI Grant
Publisher Copyright:
© 2019 IEEE.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
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 -