物联网中的数据可视化:工具、方法和挑战

Antonis I Protopsaltis, P. Sarigiannidis, Dimitrios G. Margounakis, A. Lytos
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引用次数: 25

摘要

随着物联网(IoT)的快速发展,大量无线传感器网络出现,用于监控医疗、能源、交通、智慧城市、楼宇自动化、农业和工业等各个领域的广泛基础设施,不断产生数据流。大数据技术在物联网过程中发挥着重要作用,作为可视化分析工具,实时生成有价值的知识,以支持关键决策。本文提供了物联网可视化方法、工具和技术的全面调查。我们通过回顾可视化分析管道将数据可视化置于可视化分析过程中。我们提供了用于数据可视化的各种图表类型的研究,并分析了使用每种图表类型的规则,同时考虑到特定用例的特殊条件。我们进一步研究了一些最有前途的可视化工具。由于每个物联网领域在大数据方法方面是隔离的,因此我们研究了每个领域的可视化问题。此外,我们回顾了面向异常检测的可视化方法。最后,我们概述了物联网可视化中的主要挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data visualization in internet of things: tools, methodologies, and challenges
As the Internet of Things (IoT) grows rapidly, huge amounts of wireless sensor networks emerged monitoring a wide range of infrastructure, in various domains such as healthcare, energy, transportation, smart city, building automation, agriculture, and industry producing continuously streamlines of data. Big Data technologies play a significant role within IoT processes, as visual analytics tools, generating valuable knowledge in real-time in order to support critical decision making. This paper provides a comprehensive survey of visualization methods, tools, and techniques for the IoT. We position data visualization inside the visual analytics process by reviewing the visual analytics pipeline. We provide a study of various chart types available for data visualization and analyze rules for employing each one of them, taking into account the special conditions of the particular use case. We further examine some of the most promising visualization tools. Since each IoT domain is isolated in terms of Big Data approaches, we investigate visualization issues in each domain. Additionally, we review visualization methods oriented to anomaly detection. Finally, we provide an overview of the major challenges in IoT visualizations.
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