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 , Zhaokang Gong , Jianhua Zheng , Yongxin Liu , 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 , Zhaokang Gong , Jianhua Zheng , Yongxin Liu , 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}
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.
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.