UAV-based multispectral image analysis system with semantic computing for agricultural health conditions monitoring and real-time management

Jinmika Wijitdechakul, Shiori Sasaki, Yasushi Kiyoki, Chawan Koopipat

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationProceedings - 2016 International Electronics Symposium, IES 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages459-464
Number of pages6
ISBN (Electronic)9781509016402
DOIs
Publication statusPublished - 2017 Feb 21
Event18th International Electronics Symposium, IES 2016 - Bali, Indonesia
Duration: 2016 Sep 292016 Sep 30

Other

Other18th International Electronics Symposium, IES 2016
CountryIndonesia
CityBali
Period16/9/2916/9/30

Fingerprint

Condition Monitoring
Aerial Image
Multispectral Images
Autonomous Vehicles
semantics
Condition monitoring
Health Monitoring
image analysis
Image Analysis
Image analysis
health
vehicles
Semantics
Health
Antennas
Real-time
Computing
Latvia
Disaster
Disasters

Keywords

  • Farming analysis
  • multispectral image
  • Semantic computing
  • SPA processs

ASJC Scopus subject areas

  • Computer Science Applications
  • Algebra and Number Theory
  • Electrical and Electronic Engineering
  • Instrumentation

Cite this

Wijitdechakul, J., Sasaki, S., Kiyoki, Y., & Koopipat, C. (2017). UAV-based multispectral image analysis system with semantic computing for agricultural health conditions monitoring and real-time management. In Proceedings - 2016 International Electronics Symposium, IES 2016 (pp. 459-464). [7861050] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ELECSYM.2016.7861050

UAV-based multispectral image analysis system with semantic computing for agricultural health conditions monitoring and real-time management. / Wijitdechakul, Jinmika; Sasaki, Shiori; Kiyoki, Yasushi; Koopipat, Chawan.

Proceedings - 2016 International Electronics Symposium, IES 2016. Institute of Electrical and Electronics Engineers Inc., 2017. p. 459-464 7861050.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wijitdechakul, J, Sasaki, S, Kiyoki, Y & Koopipat, C 2017, UAV-based multispectral image analysis system with semantic computing for agricultural health conditions monitoring and real-time management. in Proceedings - 2016 International Electronics Symposium, IES 2016., 7861050, Institute of Electrical and Electronics Engineers Inc., pp. 459-464, 18th International Electronics Symposium, IES 2016, Bali, Indonesia, 16/9/29. https://doi.org/10.1109/ELECSYM.2016.7861050
Wijitdechakul J, Sasaki S, Kiyoki Y, Koopipat C. UAV-based multispectral image analysis system with semantic computing for agricultural health conditions monitoring and real-time management. In Proceedings - 2016 International Electronics Symposium, IES 2016. Institute of Electrical and Electronics Engineers Inc. 2017. p. 459-464. 7861050 https://doi.org/10.1109/ELECSYM.2016.7861050
Wijitdechakul, Jinmika ; Sasaki, Shiori ; Kiyoki, Yasushi ; Koopipat, Chawan. / UAV-based multispectral image analysis system with semantic computing for agricultural health conditions monitoring and real-time management. Proceedings - 2016 International Electronics Symposium, IES 2016. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 459-464
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