TY - GEN
T1 - Early rice disease detection and position mapping system using drone and IoT architecture
AU - Kitpo, Nuttakarn
AU - Inoue, Masahiro
N1 - Funding Information:
This work was supported by JSPS KAKENHI Grant Number 15K00929.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/3
Y1 - 2018/3
N2 - Rice is the main agricultural produce in many Asian countries. However, the occurrence of diseases on rice plants could degrade the quality and decrease the quantity of rice. Therefore, earlier detection of plant disease will help preventing the rice from severe infection and avoiding crop loss. Recently, drones have been used in agriculture monitoring together with the camera and GPS sensor. It is an alternative tool to obtain data quickly and autonomously in large-scaled area. For a better rice productivity, this paper presents the implementation system of drone based on Internet of Things (IoT) architecture using real-time information including data acquisition and data analysis using image processing technique to perform rice disease detection and classification. The system is capable of displaying the analytic results including the position of infected rice plants mapping them on rice fields by using GPS sensor to define the position in real-time. This system was designed and proposed as a preliminary to support system for early and real-time disease detection with the implementation of IoT architecture.
AB - Rice is the main agricultural produce in many Asian countries. However, the occurrence of diseases on rice plants could degrade the quality and decrease the quantity of rice. Therefore, earlier detection of plant disease will help preventing the rice from severe infection and avoiding crop loss. Recently, drones have been used in agriculture monitoring together with the camera and GPS sensor. It is an alternative tool to obtain data quickly and autonomously in large-scaled area. For a better rice productivity, this paper presents the implementation system of drone based on Internet of Things (IoT) architecture using real-time information including data acquisition and data analysis using image processing technique to perform rice disease detection and classification. The system is capable of displaying the analytic results including the position of infected rice plants mapping them on rice fields by using GPS sensor to define the position in real-time. This system was designed and proposed as a preliminary to support system for early and real-time disease detection with the implementation of IoT architecture.
KW - Disease classification
KW - Disease detection
KW - Drone
KW - Image processing
KW - Position mapping
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U2 - 10.1109/SEATUC.2018.8788863
DO - 10.1109/SEATUC.2018.8788863
M3 - Conference contribution
AN - SCOPUS:85071564377
T3 - Proceedings - 12th SEATUC Symposium, SEATUC 2018
BT - Proceedings - 12th SEATUC Symposium, SEATUC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 12th South East Asian Technical University Consortium Sysmposium, SEATUC 2018
Y2 - 12 March 2018 through 13 March 2018
ER -