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物联网环境中空间分布数据的分析。

Analysis of Spatially Distributed Data in Internet of Things in the Environmental Context.

机构信息

Institute of Mathematics and Computer Science, University of São Paulo, Sao Paulo 13560-970, SP, Brazil.

School of Electronics, Computing and Maths, University of Derby, Kedleston Rd., Derby DE22 1GB, UK.

出版信息

Sensors (Basel). 2022 Feb 22;22(5):1693. doi: 10.3390/s22051693.

Abstract

The Internet of Things consists of "things" made up of small sensors and actuators capable of interacting with the environment. The combination of devices with sensor networks and Internet access enables the communication between the physical world and cyberspace, enabling the development of solutions to many real-world problems. However, most existing applications are dedicated to solving a specific problem using only private sensor networks, which limits the actual capacity of the Internet of Things. In addition, these applications are concerned with the quality of service offered by the sensor network or the correct analysis method that can lead to inaccurate or irrelevant conclusions, which can cause significant harm for decision makers. In this context, we propose two systematic methods to analyze spatially distributed data Internet of Things. We show with the results that geostatistics and spatial statistics are more appropriate than classical statistics to do this analysis.

摘要

物联网由具有交互环境能力的小型传感器和执行器组成。设备与传感器网络和互联网接入的结合使物理世界和网络空间之间的通信成为可能,从而为解决许多现实世界的问题提供了可能。然而,大多数现有的应用程序都致力于使用专用的传感器网络来解决特定的问题,这限制了物联网的实际容量。此外,这些应用程序关注的是传感器网络提供的服务质量或可以导致不准确或不相关结论的正确分析方法,这可能会给决策者造成重大危害。在这种情况下,我们提出了两种系统的方法来分析空间分布数据的物联网。我们的结果表明,地质统计学和空间统计学比经典统计学更适合进行这种分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee88/8914928/319712667a46/sensors-22-01693-g001.jpg

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