智能家居爬虫:面向半自动物联网传感器集成的框架

M. Strohbach, Luis Adan Saavedra, Pavel Smirnov, Stefaniia Legostaieva
{"title":"智能家居爬虫:面向半自动物联网传感器集成的框架","authors":"M. Strohbach, Luis Adan Saavedra, Pavel Smirnov, Stefaniia Legostaieva","doi":"10.1109/GIOTS.2019.8766394","DOIUrl":null,"url":null,"abstract":"Sensor deployments in Smart Homes have long reached commercial relevance for applications such as home automation, home safety or energy consumption awareness and reduction. Nevertheless, due to the heterogeneity of sensor devices and gateways, data integration is still a costly and time-consuming process. In this paper we propose the Smart Home Crawler Framework that (1) provides a common semantic abstraction from the underlying sensor and gateway technologies, and (2) accelerates the integration of new devices by applying machine learning techniques for linking discovered devices to a semantic data model. We present a first prototype that was demonstrated at ICT 2018. The prototype was built as a domain-specific crawling component for IoTCrawler, a secure and privacy-preserving search engine for the Internet of Things.","PeriodicalId":149504,"journal":{"name":"2019 Global IoT Summit (GIoTS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Smart Home Crawler : Towards a framework for semi-automatic IoT sensor integration\",\"authors\":\"M. Strohbach, Luis Adan Saavedra, Pavel Smirnov, Stefaniia Legostaieva\",\"doi\":\"10.1109/GIOTS.2019.8766394\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Sensor deployments in Smart Homes have long reached commercial relevance for applications such as home automation, home safety or energy consumption awareness and reduction. Nevertheless, due to the heterogeneity of sensor devices and gateways, data integration is still a costly and time-consuming process. In this paper we propose the Smart Home Crawler Framework that (1) provides a common semantic abstraction from the underlying sensor and gateway technologies, and (2) accelerates the integration of new devices by applying machine learning techniques for linking discovered devices to a semantic data model. We present a first prototype that was demonstrated at ICT 2018. The prototype was built as a domain-specific crawling component for IoTCrawler, a secure and privacy-preserving search engine for the Internet of Things.\",\"PeriodicalId\":149504,\"journal\":{\"name\":\"2019 Global IoT Summit (GIoTS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Global IoT Summit (GIoTS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GIOTS.2019.8766394\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Global IoT Summit (GIoTS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GIOTS.2019.8766394","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

智能家居中的传感器部署早已达到了家庭自动化、家庭安全或能源消耗意识和减少等应用的商业意义。然而,由于传感器设备和网关的异构性,数据集成仍然是一个昂贵且耗时的过程。在本文中,我们提出了智能家居爬虫框架,该框架(1)提供了来自底层传感器和网关技术的通用语义抽象,(2)通过应用机器学习技术将发现的设备链接到语义数据模型来加速新设备的集成。我们展示了在ICT 2018上展示的第一个原型。该原型是作为IoTCrawler的特定领域爬行组件构建的,IoTCrawler是一个安全且保护隐私的物联网搜索引擎。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Smart Home Crawler : Towards a framework for semi-automatic IoT sensor integration
Sensor deployments in Smart Homes have long reached commercial relevance for applications such as home automation, home safety or energy consumption awareness and reduction. Nevertheless, due to the heterogeneity of sensor devices and gateways, data integration is still a costly and time-consuming process. In this paper we propose the Smart Home Crawler Framework that (1) provides a common semantic abstraction from the underlying sensor and gateway technologies, and (2) accelerates the integration of new devices by applying machine learning techniques for linking discovered devices to a semantic data model. We present a first prototype that was demonstrated at ICT 2018. The prototype was built as a domain-specific crawling component for IoTCrawler, a secure and privacy-preserving search engine for the Internet of Things.
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
自引率
0.00%
发文量
0
×
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:604180095
Book学术官方微信