A Data Management Method for Remote and Long-Term Seafloor Observation System
文献类型:期刊论文
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作者 | Wang, Huacan1,2![]() ![]() ![]() ![]() |
刊名 | MARINE GEODESY
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出版日期 | 2020-01-02 ; 2020-01-02 |
卷号 | 43期号:1页码:1-22 |
关键词 | Image compression Image compression junction box satellite communication seafloor observation junction box satellite communication seafloor observation |
ISSN号 | 0149-0419 ; 0149-0419 |
DOI | 10.1080/01490419.2019.1673265 ; 10.1080/01490419.2019.1673265 |
通讯作者 | Zhang, Shaowei |
英文摘要 | The deep seafloor is closest to the Earth's interior and there are complicated interactions in the physical and biological processes of the seafloor. Oceanographic parameters such as temperature, salinity, and ocean current can provide support for climate prediction. Therefore, the long-term observation of the deep seafloor is critical to the study of global climate change and the biodiversity in complex environments. For the requirements of long-term observation and remote data transmission in the deep sea of the South China Sea, a seafloor observation prototype system is designed in this paper as a stand-alone observation platform. We then proposed a date management method based on Controller Area Network to ensure the data quality. Distributed data management can be performed through system layering, and strict data transmission standards are established between each layer. At the same time, aiming at the difficulty of seafloor video data transmission in real-time, a new solution based on satellite communication technology, object detection technology, and high-efficiency compression coding technology of video images is proposed to provide support for seafloor biodiversity research. The observation data from the experiment are given, and these results show that the system can meet the requirements of long-term observation and remote real-time data transmission, and the reliability of the system is verified. ;The deep seafloor is closest to the Earth's interior and there are complicated interactions in the physical and biological processes of the seafloor. Oceanographic parameters such as temperature, salinity, and ocean current can provide support for climate prediction. Therefore, the long-term observation of the deep seafloor is critical to the study of global climate change and the biodiversity in complex environments. For the requirements of long-term observation and remote data transmission in the deep sea of the South China Sea, a seafloor observation prototype system is designed in this paper as a stand-alone observation platform. We then proposed a date management method based on Controller Area Network to ensure the data quality. Distributed data management can be performed through system layering, and strict data transmission standards are established between each layer. At the same time, aiming at the difficulty of seafloor video data transmission in real-time, a new solution based on satellite communication technology, object detection technology, and high-efficiency compression coding technology of video images is proposed to provide support for seafloor biodiversity research. The observation data from the experiment are given, and these results show that the system can meet the requirements of long-term observation and remote real-time data transmission, and the reliability of the system is verified. |
WOS关键词 | BARKLEY CANYON ; BARKLEY CANYON ; DEEP-SEA ; CLASSIFICATION ; CHALLENGES ; BEHAVIOR ; RHYTHMS ; DEEP-SEA ; CLASSIFICATION ; CHALLENGES ; BEHAVIOR ; RHYTHMS |
资助项目 | Natural Science Foundation of China NSFC[51809255] ; Natural Science Foundation of China NSFC[51809255] ; National Key Research and Development Plan of China[2018YFC0307906] ; China Strategic Priority Research Program of the Chinese Academy of Sciences[XDA13030301] ; Institute of Deep-sea Science and Engineering, Chinese Academy of Sciences ; National Key Research and Development Plan of China[2018YFC0307906] ; China Strategic Priority Research Program of the Chinese Academy of Sciences[XDA13030301] ; Institute of Deep-sea Science and Engineering, Chinese Academy of Sciences |
WOS研究方向 | Geochemistry & Geophysics ; Geochemistry & Geophysics ; Oceanography ; Remote Sensing ; Oceanography ; Remote Sensing |
语种 | 英语 ; 英语 |
WOS记录号 | WOS:000493422500001 ; WOS:000493422500001 |
出版者 | TAYLOR & FRANCIS INC ; TAYLOR & FRANCIS INC |
资助机构 | Natural Science Foundation of China NSFC ; Natural Science Foundation of China NSFC ; National Key Research and Development Plan of China ; China Strategic Priority Research Program of the Chinese Academy of Sciences ; Institute of Deep-sea Science and Engineering, Chinese Academy of Sciences ; National Key Research and Development Plan of China ; China Strategic Priority Research Program of the Chinese Academy of Sciences ; Institute of Deep-sea Science and Engineering, Chinese Academy of Sciences |
版本 | 出版稿 |
源URL | [http://ir.idsse.ac.cn/handle/183446/7426] ![]() |
专题 | 研究生部 深海工程技术部_深海探测技术研究室 |
通讯作者 | Zhang, Shaowei |
作者单位 | 1.Chinese Acad Sci, Inst Deep Sea Sci & Engn, Sanya 572000, Hainan, Peoples R China 2.Univ Chinese Acad Sci, Coll Mat Sci & Optoelect Technol, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Wang, Huacan,Yang, Wencai,Xin, Yongzhi,et al. A Data Management Method for Remote and Long-Term Seafloor Observation System, A Data Management Method for Remote and Long-Term Seafloor Observation System[J]. MARINE GEODESY, MARINE GEODESY,2020, 2020,43, 43(1):1-22, 1-22. |
APA | Wang, Huacan,Yang, Wencai,Xin, Yongzhi,&Zhang, Shaowei.(2020).A Data Management Method for Remote and Long-Term Seafloor Observation System.MARINE GEODESY,43(1),1-22. |
MLA | Wang, Huacan,et al."A Data Management Method for Remote and Long-Term Seafloor Observation System".MARINE GEODESY 43.1(2020):1-22. |
入库方式: OAI收割
来源:深海科学与工程研究所
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