Feature-Centric Video Transmission and Analytics in Large-Scale Internet of Video Things
The interconnection of large-scale visual sensors is called the Internet of Video Things (IoVT), which brings a qualitative leap to the interaction of urban information. However, communication delay and resource allocation have brought challenges to the development of IoVT. In this paper, we propose...
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| Format: | Article |
| Language: | English |
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Tsinghua University Press
2024-12-01
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| Series: | CAAI Artificial Intelligence Research |
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| Online Access: | https://www.sciopen.com/article/10.26599/AIR.2024.9150028 |
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| author | Hongan Wei Yuxiang Liu Kejian Hu Liqun Lin Youjia Chen Tiesong Zhao Wanjian Feng |
| author_facet | Hongan Wei Yuxiang Liu Kejian Hu Liqun Lin Youjia Chen Tiesong Zhao Wanjian Feng |
| author_sort | Hongan Wei |
| collection | DOAJ |
| description | The interconnection of large-scale visual sensors is called the Internet of Video Things (IoVT), which brings a qualitative leap to the interaction of urban information. However, communication delay and resource allocation have brought challenges to the development of IoVT. In this paper, we propose a novel city surveillance IoVT architecture to improve performance. This paradigm consists of front-end target region capture, edge computing and cloud-end feature matching, which can adapt the channel and computing resource allocation ratio flexibly, avoiding communication link congestion caused by unnecessary video uploading. Simulation results show that the proposed scheme is feasible, and can realize efficient data transmission and analysis in an IoVT-based smart city. |
| format | Article |
| id | doaj-art-4659849070cc4c9bbf417a3d05cb915d |
| institution | Kabale University |
| issn | 2097-194X 2097-3691 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Tsinghua University Press |
| record_format | Article |
| series | CAAI Artificial Intelligence Research |
| spelling | doaj-art-4659849070cc4c9bbf417a3d05cb915d2025-01-10T06:44:32ZengTsinghua University PressCAAI Artificial Intelligence Research2097-194X2097-36912024-12-013915002810.26599/AIR.2024.9150028Feature-Centric Video Transmission and Analytics in Large-Scale Internet of Video ThingsHongan Wei0Yuxiang Liu1Kejian Hu2Liqun Lin3Youjia Chen4Tiesong Zhao5Wanjian Feng6Fujian Key Lab for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fuzhou University, Fuzhou 350116, ChinaFujian Key Lab for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fuzhou University, Fuzhou 350116, ChinaFujian Key Lab for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fuzhou University, Fuzhou 350116, ChinaFujian Key Lab for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fuzhou University, Fuzhou 350116, ChinaFujian Key Lab for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fuzhou University, Fuzhou 350116, ChinaFujian Key Lab for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fuzhou University, Fuzhou 350116, ChinaYealink Inc., Xiamen 361009, ChinaThe interconnection of large-scale visual sensors is called the Internet of Video Things (IoVT), which brings a qualitative leap to the interaction of urban information. However, communication delay and resource allocation have brought challenges to the development of IoVT. In this paper, we propose a novel city surveillance IoVT architecture to improve performance. This paradigm consists of front-end target region capture, edge computing and cloud-end feature matching, which can adapt the channel and computing resource allocation ratio flexibly, avoiding communication link congestion caused by unnecessary video uploading. Simulation results show that the proposed scheme is feasible, and can realize efficient data transmission and analysis in an IoVT-based smart city.https://www.sciopen.com/article/10.26599/AIR.2024.9150028internet of video things (iovt)edge computingvideo transmissionresource allocation |
| spellingShingle | Hongan Wei Yuxiang Liu Kejian Hu Liqun Lin Youjia Chen Tiesong Zhao Wanjian Feng Feature-Centric Video Transmission and Analytics in Large-Scale Internet of Video Things CAAI Artificial Intelligence Research internet of video things (iovt) edge computing video transmission resource allocation |
| title | Feature-Centric Video Transmission and Analytics in Large-Scale Internet of Video Things |
| title_full | Feature-Centric Video Transmission and Analytics in Large-Scale Internet of Video Things |
| title_fullStr | Feature-Centric Video Transmission and Analytics in Large-Scale Internet of Video Things |
| title_full_unstemmed | Feature-Centric Video Transmission and Analytics in Large-Scale Internet of Video Things |
| title_short | Feature-Centric Video Transmission and Analytics in Large-Scale Internet of Video Things |
| title_sort | feature centric video transmission and analytics in large scale internet of video things |
| topic | internet of video things (iovt) edge computing video transmission resource allocation |
| url | https://www.sciopen.com/article/10.26599/AIR.2024.9150028 |
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