From Limited Resources to Powerful Insights: Empowering Low-Cost Cameras for Efficient Retrospective Querying

doi:10.1109/JIOT.2024.3480089

	From Limited Resources to Powerful Insights: Empowering Low-Cost Cameras for Efficient Retrospective Querying
	Wen, Qiaodi 1,2; Zhou, Jianer 2; Chen, Ruitao 1; Luo, Ziqi 1; Tyson, Gareth 3; Li, Weichao 2; Wang, Jinfan 4,5; Pan, Heng 6; Xu, Zhiwei 7,8
	2025-02-01
发表期刊	IEEE INTERNET OF THINGS JOURNAL
ISSN	2327-4662
卷号	12 期号:3 页码:2825-2837
摘要	Uploading videos from low-cost cameras to the cloud for retrospective analysis presents challenges in privacy, network, and computation. To address these issues and achieve low latency, we propose READY, a novel client-cloud collaborative system. READY aims to enhance the quality of uploaded frames by selectively uploading only the frames relevant to queries. To achieve this, READY establishes an index during video capture, recording object categories and probabilities for each frame. READY adopts an innovative semi-supervised approach for frame indexing, wherein frames are indexed through a continuously updated feature distribution space constructed by k-nearest neighbors (KNN). This enables resource-constrained low-cost cameras to independently establish long-term frame indexes. Additionally, READY utilizes progressively improving operators (lightweight classification models) dispatched by the cloud to optimize the upload order of frames, prioritizing positive frames. By sharing the backbone of low-performance operators, high-performance operators can be efficiently executed, significantly enhancing the camera's frame processing capability. The established frame index also enables efficient multiple consecutive queries on different classes. Over 110 h of diverse queries across 11 videos, READY outperformed competing alternative designs by achieving an average response time of 67.8% and reducing the proportion of uploaded videos by an average of 79.8% (compared to CloudOnly).
关键词	Cameras Videos Cloud computing Accuracy Nearest neighbor methods Costs Indexing Training Electronic mail Collaboration k-nearest neighbors (KNN) low-cost cameras retrospective queries video analytics
DOI	10.1109/JIOT.2024.3480089
收录类别	SCI
语种	英语
资助项目	Major Key Project of PCL[PCL2024Y02] ; Major Key Project of PCL[PCL2023AS1-5] ; Major Key Project of PCL[PCL2023AS1-3] ; Program for Young Talents of Science and Technology in Universities of Inner Mongolia Autonomous Region[NJYT23104] ; Basic Scientific Research Expenses Program of Universities directly under Inner Mongolia Autonomous Region[JY20220273] ; Basic Scientific Research Expenses Program of Universities directly under Inner Mongolia Autonomous Region[JY20240002]
WOS研究方向	Computer Science ; Engineering ; Telecommunications
WOS类目	Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS记录号	WOS:001407270600034
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/40765
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Zhou, Jianer
作者单位	1.Southern Univ Sci & Technol, Shenzhen 518055, Peoples R China 2.Peng Cheng Lab, Shenzhen 518066, Peoples R China 3.Hong Kong Univ Sci & Technol Guangzhou, Guangzhou 511453, Peoples R China 4.Southern Univ Sci & Technol, Inst Future Networks, Shenzhen 518055, Peoples R China 5.Linkinsense Anhui Ltd, Hefei, Peoples R China 6.Chinese Acad Sci, Comp Network Informat Ctr, Beijing 100045, Peoples R China 7.Haihe Lab Informat Technol Applicat Innovat, Tianjin 300459, Peoples R China 8.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Wen, Qiaodi,Zhou, Jianer,Chen, Ruitao,et al. From Limited Resources to Powerful Insights: Empowering Low-Cost Cameras for Efficient Retrospective Querying[J]. IEEE INTERNET OF THINGS JOURNAL,2025,12(3):2825-2837.
APA	Wen, Qiaodi.,Zhou, Jianer.,Chen, Ruitao.,Luo, Ziqi.,Tyson, Gareth.,...&Xu, Zhiwei.(2025).From Limited Resources to Powerful Insights: Empowering Low-Cost Cameras for Efficient Retrospective Querying.IEEE INTERNET OF THINGS JOURNAL,12(3),2825-2837.
MLA	Wen, Qiaodi,et al."From Limited Resources to Powerful Insights: Empowering Low-Cost Cameras for Efficient Retrospective Querying".IEEE INTERNET OF THINGS JOURNAL 12.3(2025):2825-2837.