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 proceedingConference contribution

14 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 languageEnglish
Title of host publication2019 IEEE International Conference on Consumer Electronics, ICCE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538679104
DOIs
Publication statusPublished - 2019 Mar 6
Event2019 IEEE International Conference on Consumer Electronics, ICCE 2019 - Las Vegas, United States
Duration: 2019 Jan 112019 Jan 13

Publication series

Name2019 IEEE International Conference on Consumer Electronics, ICCE 2019

Conference

Conference2019 IEEE International Conference on Consumer Electronics, ICCE 2019
Country/TerritoryUnited States
CityLas Vegas
Period19/1/1119/1/13

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

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