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Intelligent fish farm—the future of aquaculture
With the continuous expansion of aquaculture scale and density, contemporary aquaculture methods have been forced to overproduce resulting in the accelerated imbalance rate of water environment, the frequent occurrence of fish diseases, and the decline of aquatic product quality. Moreover, due to th...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8435764/ https://www.ncbi.nlm.nih.gov/pubmed/34539102 http://dx.doi.org/10.1007/s10499-021-00773-8 |
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author | Wang, Cong Li, Zhen Wang, Tan Xu, Xianbao Zhang, Xiaoshuan Li, Daoliang |
author_facet | Wang, Cong Li, Zhen Wang, Tan Xu, Xianbao Zhang, Xiaoshuan Li, Daoliang |
author_sort | Wang, Cong |
collection | PubMed |
description | With the continuous expansion of aquaculture scale and density, contemporary aquaculture methods have been forced to overproduce resulting in the accelerated imbalance rate of water environment, the frequent occurrence of fish diseases, and the decline of aquatic product quality. Moreover, due to the fact that the average age profile of agricultural workers in many parts of the world are on the higher side, fishery production will face the dilemma of shortage of labor, and aquaculture methods are in urgent need of change. Modern information technology has gradually penetrated into various fields of agriculture, and the concept of intelligent fish farm has also begun to take shape. The intelligent fish farm tries to deal with the precise work of increasing oxygen, optimizing feeding, reducing disease incidences, and accurately harvesting through the idea of “replacing human with machine,” so as to liberate the manpower completely and realize the green and sustainable aquaculture. This paper reviews the application of fishery intelligent equipment, IoT, edge computing, 5G, and artificial intelligence algorithms in modern aquaculture, and analyzes the existing problems and future development prospects. Meanwhile, based on different business requirements, the design frameworks for key functional modules in the construction of intelligent fish farm are proposed. |
format | Online Article Text |
id | pubmed-8435764 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-84357642021-09-13 Intelligent fish farm—the future of aquaculture Wang, Cong Li, Zhen Wang, Tan Xu, Xianbao Zhang, Xiaoshuan Li, Daoliang Aquac Int Article With the continuous expansion of aquaculture scale and density, contemporary aquaculture methods have been forced to overproduce resulting in the accelerated imbalance rate of water environment, the frequent occurrence of fish diseases, and the decline of aquatic product quality. Moreover, due to the fact that the average age profile of agricultural workers in many parts of the world are on the higher side, fishery production will face the dilemma of shortage of labor, and aquaculture methods are in urgent need of change. Modern information technology has gradually penetrated into various fields of agriculture, and the concept of intelligent fish farm has also begun to take shape. The intelligent fish farm tries to deal with the precise work of increasing oxygen, optimizing feeding, reducing disease incidences, and accurately harvesting through the idea of “replacing human with machine,” so as to liberate the manpower completely and realize the green and sustainable aquaculture. This paper reviews the application of fishery intelligent equipment, IoT, edge computing, 5G, and artificial intelligence algorithms in modern aquaculture, and analyzes the existing problems and future development prospects. Meanwhile, based on different business requirements, the design frameworks for key functional modules in the construction of intelligent fish farm are proposed. Springer International Publishing 2021-09-13 2021 /pmc/articles/PMC8435764/ /pubmed/34539102 http://dx.doi.org/10.1007/s10499-021-00773-8 Text en © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Wang, Cong Li, Zhen Wang, Tan Xu, Xianbao Zhang, Xiaoshuan Li, Daoliang Intelligent fish farm—the future of aquaculture |
title | Intelligent fish farm—the future of aquaculture |
title_full | Intelligent fish farm—the future of aquaculture |
title_fullStr | Intelligent fish farm—the future of aquaculture |
title_full_unstemmed | Intelligent fish farm—the future of aquaculture |
title_short | Intelligent fish farm—the future of aquaculture |
title_sort | intelligent fish farm—the future of aquaculture |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8435764/ https://www.ncbi.nlm.nih.gov/pubmed/34539102 http://dx.doi.org/10.1007/s10499-021-00773-8 |
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