智能农业数据协作传感方法调查

IF 6 3区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Xiaomin Li , Zhaokang Gong , Jianhua Zheng , Yongxin Liu , Huiru Cao
{"title":"智能农业数据协作传感方法调查","authors":"Xiaomin Li ,&nbsp;Zhaokang Gong ,&nbsp;Jianhua Zheng ,&nbsp;Yongxin Liu ,&nbsp;Huiru Cao","doi":"10.1016/j.iot.2024.101354","DOIUrl":null,"url":null,"abstract":"<div><p>Data is becoming increasingly pivotal and foundational in the development of smart agriculture, underscoring the importance of efficient methods for obtaining high-value data. Data sensing methods have become the key technologies and methods to realize the agricultural Internet of Things (IoT). However, in the face of the new agricultural paradigm driven by big data, traditional agricultural IoT confronts numerous challenges at the data sensing level. This article, therefore, adopts a data sensing perspective and, based on the agricultural IoT, explores the evolution of data sensing technology in the agricultural domain. Initially, it introduces a data sensing framework for the agricultural Internet of Things, which integrates cloud and edge computing. Subsequently, it reviews the sensors commonly deployed in agricultural scenarios. Then, common methods for collaborative sensing of agricultural data were discussed from three aspects: intra-node, multiple nodes, and cross-domain. At the same time, the issues of data security and privacy in data collaborative sensing were discussed. Next, we integrate multi-dimensional technology to construct an application case for data sensing in the agricultural IoT. Finally, it discusses the challenges that Collaborative sensing technology encounters within the agricultural IoT.</p></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":"28 ","pages":"Article 101354"},"PeriodicalIF":6.0000,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A survey of data collaborative sensing methods for smart agriculture\",\"authors\":\"Xiaomin Li ,&nbsp;Zhaokang Gong ,&nbsp;Jianhua Zheng ,&nbsp;Yongxin Liu ,&nbsp;Huiru Cao\",\"doi\":\"10.1016/j.iot.2024.101354\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Data is becoming increasingly pivotal and foundational in the development of smart agriculture, underscoring the importance of efficient methods for obtaining high-value data. Data sensing methods have become the key technologies and methods to realize the agricultural Internet of Things (IoT). However, in the face of the new agricultural paradigm driven by big data, traditional agricultural IoT confronts numerous challenges at the data sensing level. This article, therefore, adopts a data sensing perspective and, based on the agricultural IoT, explores the evolution of data sensing technology in the agricultural domain. Initially, it introduces a data sensing framework for the agricultural Internet of Things, which integrates cloud and edge computing. Subsequently, it reviews the sensors commonly deployed in agricultural scenarios. Then, common methods for collaborative sensing of agricultural data were discussed from three aspects: intra-node, multiple nodes, and cross-domain. At the same time, the issues of data security and privacy in data collaborative sensing were discussed. Next, we integrate multi-dimensional technology to construct an application case for data sensing in the agricultural IoT. Finally, it discusses the challenges that Collaborative sensing technology encounters within the agricultural IoT.</p></div>\",\"PeriodicalId\":29968,\"journal\":{\"name\":\"Internet of Things\",\"volume\":\"28 \",\"pages\":\"Article 101354\"},\"PeriodicalIF\":6.0000,\"publicationDate\":\"2024-08-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Internet of Things\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2542660524002956\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Internet of Things","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2542660524002956","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

摘要

数据在智慧农业的发展中越来越具有关键性和基础性作用,这凸显了高效获取高价值数据方法的重要性。数据传感方法已成为实现农业物联网的关键技术和方法。然而,面对大数据驱动的新型农业模式,传统农业物联网在数据传感层面面临诸多挑战。因此,本文采用数据传感视角,以农业物联网为基础,探讨数据传感技术在农业领域的发展。文章首先介绍了农业物联网的数据传感框架,该框架集成了云计算和边缘计算。随后,它回顾了农业场景中通常部署的传感器。然后,从节点内、多节点和跨域三个方面讨论了农业数据协同感知的常用方法。同时,讨论了数据协同感知中的数据安全和隐私问题。其次,结合多维技术,构建了农业物联网中数据感知的应用案例。最后,讨论了协作传感技术在农业物联网中遇到的挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A survey of data collaborative sensing methods for smart agriculture

Data is becoming increasingly pivotal and foundational in the development of smart agriculture, underscoring the importance of efficient methods for obtaining high-value data. Data sensing methods have become the key technologies and methods to realize the agricultural Internet of Things (IoT). However, in the face of the new agricultural paradigm driven by big data, traditional agricultural IoT confronts numerous challenges at the data sensing level. This article, therefore, adopts a data sensing perspective and, based on the agricultural IoT, explores the evolution of data sensing technology in the agricultural domain. Initially, it introduces a data sensing framework for the agricultural Internet of Things, which integrates cloud and edge computing. Subsequently, it reviews the sensors commonly deployed in agricultural scenarios. Then, common methods for collaborative sensing of agricultural data were discussed from three aspects: intra-node, multiple nodes, and cross-domain. At the same time, the issues of data security and privacy in data collaborative sensing were discussed. Next, we integrate multi-dimensional technology to construct an application case for data sensing in the agricultural IoT. Finally, it discusses the challenges that Collaborative sensing technology encounters within the agricultural IoT.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Internet of Things
Internet of Things Multiple-
CiteScore
3.60
自引率
5.10%
发文量
115
审稿时长
37 days
期刊介绍: Internet of Things; Engineering Cyber Physical Human Systems is a comprehensive journal encouraging cross collaboration between researchers, engineers and practitioners in the field of IoT & Cyber Physical Human Systems. The journal offers a unique platform to exchange scientific information on the entire breadth of technology, science, and societal applications of the IoT. The journal will place a high priority on timely publication, and provide a home for high quality. Furthermore, IOT is interested in publishing topical Special Issues on any aspect of IOT.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信