TY - GEN
T1 - UAV-based multispectral image analysis system with semantic computing for agricultural health conditions monitoring and real-time management
AU - Wijitdechakul, Jinmika
AU - Sasaki, Shiori
AU - Kiyoki, Yasushi
AU - Koopipat, Chawan
N1 - Funding Information:
This research is supported in part by MEXT Grant-in-Aid for the Program for Leading Graduate School Program (GESL) and Multimedia Database Laboratory (MDBL), Graduate School of Media and Governance, Keio University. We thank the anonymous reviewers for their valuable comment and suggestions.
Publisher Copyright:
© 2016 IEEE.
PY - 2017/2/21
Y1 - 2017/2/21
N2 - Nowadays, UAV is widely used in several research and industrial fields. One of the highly beneficial features is that it is able to be utilized to capture aerial images in high-resolution for environmental study or detecting disaster phenomena quickly. This paper presents a multispectral image analysis system for aerial images that captured by multispectral camera, which are mounted on an unmanned autonomous vehicle (UAV) or Drone, and discusses an application of semantic computing system for agricultural health condition monitoring and analysis. In our experiments, we analyze multispectral images to detect healthy and unhealthy conditions of agricultural area and interpret the keyword of plant health conditions for user. We also propose the SPA process for real-time farming area management. As a case study, we conducted an experiment on rye fields in Latvia.
AB - Nowadays, UAV is widely used in several research and industrial fields. One of the highly beneficial features is that it is able to be utilized to capture aerial images in high-resolution for environmental study or detecting disaster phenomena quickly. This paper presents a multispectral image analysis system for aerial images that captured by multispectral camera, which are mounted on an unmanned autonomous vehicle (UAV) or Drone, and discusses an application of semantic computing system for agricultural health condition monitoring and analysis. In our experiments, we analyze multispectral images to detect healthy and unhealthy conditions of agricultural area and interpret the keyword of plant health conditions for user. We also propose the SPA process for real-time farming area management. As a case study, we conducted an experiment on rye fields in Latvia.
KW - Farming analysis
KW - SPA processs
KW - Semantic computing
KW - multispectral image
UR - http://www.scopus.com/inward/record.url?scp=85031995700&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85031995700&partnerID=8YFLogxK
U2 - 10.1109/ELECSYM.2016.7861050
DO - 10.1109/ELECSYM.2016.7861050
M3 - Conference contribution
AN - SCOPUS:85031995700
T3 - Proceedings - 2016 International Electronics Symposium, IES 2016
SP - 459
EP - 464
BT - Proceedings - 2016 International Electronics Symposium, IES 2016
A2 - Briantoro, Hendy
A2 - Zainudin, Ahmad
A2 - Permatasari, Desy Intan
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 18th International Electronics Symposium, IES 2016
Y2 - 29 September 2016 through 30 September 2016
ER -