A Blockchain-Based Approach To Enable Remote Sensing Trusted Data

Miguel Pincheira, Elena Donini, R. Giaffreda, M. Vecchio
{"title":"A Blockchain-Based Approach To Enable Remote Sensing Trusted Data","authors":"Miguel Pincheira, Elena Donini, R. Giaffreda, M. Vecchio","doi":"10.1109/LAGIRS48042.2020.9165589","DOIUrl":null,"url":null,"abstract":"Remote sensing considerably benefits from the fusion of open data from different sources, including far-range sensors mounted on satellites and short-range sensors on drones or Internet of Things devices. Open data is an emerging philosophy attracting an increasing number of data owners willing to share. However, most of the data owners are unknown and thus, untrustable, which makes shared data likely unreliable and possibly compromising associated outcomes. Currently, there exist tools that distribute open data, acting as intermediaries connecting data owners and users. However, these tools are managed by central authorities that set rules for data ownership, access, and integrity, limiting data owners and users. Therefore, a need emerges for a decentralized system to share and retrieve data without intermediaries limiting participants. Here, we propose a blockchain-based system to share and retrieve data without the need for a central authority. The proposed architecture (i) allows sharing data, (ii) maintains the data history (origin and updates), and (iii) allows retrieving and evaluating the data adding trustworthiness. To this end, the blockchain network enables the direct connection of data owners and users. Furthermore, blockchain automatically interacts with participants and keeps a transparent record of their actions. Hence, blockchain provides a decentralized database that enables trust among the participants without a central authority. We analyzed the potentials and critical issues of the architecture in a remote sensing use case of precision farming. The analysis shows that participants benefit from the properties of the blockchain in providing trusted data for remote sensing applications.","PeriodicalId":111863,"journal":{"name":"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LAGIRS48042.2020.9165589","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

Abstract

Remote sensing considerably benefits from the fusion of open data from different sources, including far-range sensors mounted on satellites and short-range sensors on drones or Internet of Things devices. Open data is an emerging philosophy attracting an increasing number of data owners willing to share. However, most of the data owners are unknown and thus, untrustable, which makes shared data likely unreliable and possibly compromising associated outcomes. Currently, there exist tools that distribute open data, acting as intermediaries connecting data owners and users. However, these tools are managed by central authorities that set rules for data ownership, access, and integrity, limiting data owners and users. Therefore, a need emerges for a decentralized system to share and retrieve data without intermediaries limiting participants. Here, we propose a blockchain-based system to share and retrieve data without the need for a central authority. The proposed architecture (i) allows sharing data, (ii) maintains the data history (origin and updates), and (iii) allows retrieving and evaluating the data adding trustworthiness. To this end, the blockchain network enables the direct connection of data owners and users. Furthermore, blockchain automatically interacts with participants and keeps a transparent record of their actions. Hence, blockchain provides a decentralized database that enables trust among the participants without a central authority. We analyzed the potentials and critical issues of the architecture in a remote sensing use case of precision farming. The analysis shows that participants benefit from the properties of the blockchain in providing trusted data for remote sensing applications.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于区块链的方法实现遥感可信数据
遥感从不同来源的开放数据融合中受益匪浅,包括安装在卫星上的远程传感器和无人机或物联网设备上的短程传感器。开放数据是一种新兴的理念,吸引了越来越多愿意分享的数据所有者。然而,大多数数据所有者是未知的,因此是不可信任的,这使得共享数据可能不可靠,并可能损害相关结果。目前,存在分发开放数据的工具,充当连接数据所有者和用户的中介。但是,这些工具由中央机构管理,中央机构为数据所有权、访问和完整性设置规则,从而限制了数据所有者和用户。因此,需要一个分散的系统来共享和检索数据,而不需要中介来限制参与者。在这里,我们提出了一个基于区块链的系统来共享和检索数据,而不需要中央机构。所提出的架构(i)允许共享数据,(ii)维护数据历史(起源和更新),以及(iii)允许检索和评估数据,增加可信度。为此,区块链网络实现了数据所有者和用户的直接连接。此外,区块链自动与参与者交互,并保持他们行为的透明记录。因此,区块链提供了一个分散的数据库,可以在没有中央权威的情况下实现参与者之间的信任。我们分析了该架构在精准农业遥感用例中的潜力和关键问题。分析表明,参与者在为遥感应用提供可信数据方面受益于区块链的特性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Deforestation Polygon Assessment Tool: Providing Comprehensive Information On Deforestation In The Brazilian Cerrado Biome Assessment of rainfall influence on sentinel-1 time series on amazonian tropical forests aiming deforestation detection improvement Spatial Association To Characterize The Climate Teleconnection Patterns In Ecuador Based On Satellite Precipitation Estimates Subsidence in Maceio, Brazil, Characterized by Dinsar and Inverse Modeling Preliminary Analysis For Automatic Tidal Inlets Mapping Using Google Earth Engine
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1