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Early Detection System of Harmful Algal Bloom Using Drones and Water Sample Image Recognition
http://hdl.handle.net/10069/40011
http://hdl.handle.net/10069/40011f21e855f-e864-4105-8af3-fc8035bdb63f
名前 / ファイル | ライセンス | アクション |
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SenMet31_4155.pdf (2.3 MB)
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Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2020-05-29 | |||||
タイトル | ||||||
タイトル | Early Detection System of Harmful Algal Bloom Using Drones and Water Sample Image Recognition | |||||
言語 | ||||||
言語 | eng | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Convolutional neural network (CNN) | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Drone | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Harmful algal bloom | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Image recognition | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Web application | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | journal article | |||||
著者 |
Kimura, Fukuyoshi
× Kimura, Fukuyoshi× Morinaga, Akihiro× Fukushima, Masayoshi× Ishiguro, Tomonari× Sato, Yasuhiko× Sakaguchi, Akihiro× Kawashita, Tomoyuki× Yamamoto, Ikuo× Kobayashi, Toru |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | Food consumption is increasing as the world population increases. While the eating of fish is spreading worldwide, the depletion of fishery resources has become a problem owing to overfishing, and the importance of aquaculture is increasing in order to continue to supply fish as food. In marine aquaculture, fish are grown in aquaculture cages in the sea. Thus, if a harmful algal bloom (HAB) reaches the cages, it will cause serious damage. Countermeasures against HAB are one of the important problems for aquaculture fishermen. In Nagasaki Prefecture in Japan, countermeasures against HAB include patrolling and sampling water by ships. These samples are then submitted to HAB experts for analysis. Following this analysis, notification is provided to aquaculture fishermen. When HAB is detected early, aquaculture fishermen can minimize the damage of HAB by stopping feeding and moving the aquaculture cages. In this study, we developed a system of early detection and notification of HAB to aquaculture fishermen. This is carried out by patrolling and sampling water using drones, detection of HAB by microscope and PC operation, and automatic notification by email and web application. As a result of this developed system, the identification accuracy of harmful plankton is more than 90%, and the time taken to find HABs can be shortened from the 6 h of the conventional approach to 15 min using this newly developed system. | |||||
書誌情報 |
Sensors and Materials 巻 31, 号 12, p. 4155-4171, 発行日 2019-12-26 |
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出版者 | ||||||
出版者 | M Y U Scientific Publishing Division | |||||
ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 09144935 | |||||
DOI | ||||||
関連タイプ | isIdenticalTo | |||||
識別子タイプ | DOI | |||||
関連識別子 | 10.18494/SAM.2019.2417 | |||||
権利 | ||||||
権利情報 | c 2019 M Y U Scientific Publishing Division. This work is licensed under a Creative Commons Attribution 4.0 International License. Sensors and Materials, Vol.31 No.12, pp.4155-4171, and DOI:10.18494/SAM.2019.2417 | |||||
著者版フラグ | ||||||
出版タイプ | VoR | |||||
出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
引用 | ||||||
内容記述タイプ | Other | |||||
内容記述 | Sensors and Materials, 31(12), pp.4155-4171; 2019 |