认知物联网(CIoT)是数据收集的成功

F. Fayaz, A. Malik, Arshad Ahmad Yatoo
{"title":"认知物联网(CIoT)是数据收集的成功","authors":"F. Fayaz, A. Malik, Arshad Ahmad Yatoo","doi":"10.1109/ICIIP53038.2021.9702706","DOIUrl":null,"url":null,"abstract":"In conjunction with data generated by intelligent machines, cognitive IoT uses cognitive computing technology and the actions these devices can accomplish. The Cognitive Internet of Things (CIoT) is seen as the new IoT is combined with mental and mutual frameworks to facilitate success and intelligence. This leading research area has recently emerged as intelligent sensing. Researchers examine the sensing data performance problems with Smarter technologies, in which people usually use smart gadgets, contribute training datasets towards the Cognitive Internet of things collected by sensors. Moreover, Cognitive Intent of Things (CIOT), shortcomings in the scope of sensing data, contribute to the loss of human life and civil instability. To answer this problem, we propose a new metric in this article, called the Quality of Information Coverage (QIC), which will personify information distribution and data sensing incentives to leverage the QIC. In addition, a market-based compensation system is being developed to pledge the QIC. To produce optimum kickbacks for CIoT and news outlets, we evaluate the optimal business solution and examine an acceptable representation. Then, by detailed computations, the results of a competition reward system are studied. The findings suggest that the way the method of reward management hits the balance point with a greater QIC than most current systems. The QIC told a system in this work guarantees that, relative to existing algorithms, the sample variance number obtained datasets for specific regions decreases by approximately less than 40 to 55 percent since these data sets are calibrated. Compared to these non-QIC-aware algorithms, the average sale price is Sensing proposed should be less than 17 to 18 percent.","PeriodicalId":431272,"journal":{"name":"2021 Sixth International Conference on Image Information Processing (ICIIP)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Cognitive Internet of things (CIoT) a success for data collection\",\"authors\":\"F. Fayaz, A. Malik, Arshad Ahmad Yatoo\",\"doi\":\"10.1109/ICIIP53038.2021.9702706\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In conjunction with data generated by intelligent machines, cognitive IoT uses cognitive computing technology and the actions these devices can accomplish. The Cognitive Internet of Things (CIoT) is seen as the new IoT is combined with mental and mutual frameworks to facilitate success and intelligence. This leading research area has recently emerged as intelligent sensing. Researchers examine the sensing data performance problems with Smarter technologies, in which people usually use smart gadgets, contribute training datasets towards the Cognitive Internet of things collected by sensors. Moreover, Cognitive Intent of Things (CIOT), shortcomings in the scope of sensing data, contribute to the loss of human life and civil instability. To answer this problem, we propose a new metric in this article, called the Quality of Information Coverage (QIC), which will personify information distribution and data sensing incentives to leverage the QIC. In addition, a market-based compensation system is being developed to pledge the QIC. To produce optimum kickbacks for CIoT and news outlets, we evaluate the optimal business solution and examine an acceptable representation. Then, by detailed computations, the results of a competition reward system are studied. The findings suggest that the way the method of reward management hits the balance point with a greater QIC than most current systems. The QIC told a system in this work guarantees that, relative to existing algorithms, the sample variance number obtained datasets for specific regions decreases by approximately less than 40 to 55 percent since these data sets are calibrated. Compared to these non-QIC-aware algorithms, the average sale price is Sensing proposed should be less than 17 to 18 percent.\",\"PeriodicalId\":431272,\"journal\":{\"name\":\"2021 Sixth International Conference on Image Information Processing (ICIIP)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 Sixth International Conference on Image Information Processing (ICIIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIIP53038.2021.9702706\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Sixth International Conference on Image Information Processing (ICIIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIIP53038.2021.9702706","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

结合智能机器产生的数据,认知物联网使用认知计算技术和这些设备可以完成的动作。认知物联网(CIoT)被视为与精神和相互框架相结合的新物联网,以促进成功和智能。这一领先的研究领域最近出现了智能传感。研究人员研究了智能技术的传感数据性能问题,其中人们通常使用智能设备,为传感器收集的认知物联网提供训练数据集。此外,物的认知意图(CIOT),在传感数据的范围内的缺点,导致人命损失和社会不稳定。为了回答这个问题,我们在本文中提出了一个新的度量标准,称为信息覆盖质量(QIC),它将个性化信息分布和数据感知激励,以利用QIC。此外,政府正在制定一个以市场为基础的补偿制度,以质押QIC。为了给CIoT和新闻媒体带来最优的回扣,我们评估了最优的业务解决方案,并检查了一个可接受的表示。然后,通过详细的计算,研究了一种竞争奖励制度的结果。研究结果表明,与大多数现有系统相比,奖励管理方法达到了更高的QIC平衡点。QIC告诉系统,在这项工作中,相对于现有算法,获得的特定区域数据集的样本方差数减少了大约不到40%到55%,因为这些数据集是经过校准的。与这些非质量感知算法相比,传感提出的平均销售价格应低于17%至18%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cognitive Internet of things (CIoT) a success for data collection
In conjunction with data generated by intelligent machines, cognitive IoT uses cognitive computing technology and the actions these devices can accomplish. The Cognitive Internet of Things (CIoT) is seen as the new IoT is combined with mental and mutual frameworks to facilitate success and intelligence. This leading research area has recently emerged as intelligent sensing. Researchers examine the sensing data performance problems with Smarter technologies, in which people usually use smart gadgets, contribute training datasets towards the Cognitive Internet of things collected by sensors. Moreover, Cognitive Intent of Things (CIOT), shortcomings in the scope of sensing data, contribute to the loss of human life and civil instability. To answer this problem, we propose a new metric in this article, called the Quality of Information Coverage (QIC), which will personify information distribution and data sensing incentives to leverage the QIC. In addition, a market-based compensation system is being developed to pledge the QIC. To produce optimum kickbacks for CIoT and news outlets, we evaluate the optimal business solution and examine an acceptable representation. Then, by detailed computations, the results of a competition reward system are studied. The findings suggest that the way the method of reward management hits the balance point with a greater QIC than most current systems. The QIC told a system in this work guarantees that, relative to existing algorithms, the sample variance number obtained datasets for specific regions decreases by approximately less than 40 to 55 percent since these data sets are calibrated. Compared to these non-QIC-aware algorithms, the average sale price is Sensing proposed should be less than 17 to 18 percent.
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:481959085
Book学术官方微信