万物互联和机器学习应用:问题与挑战

Omid Ameri Sianaki, A. Yousefi, A. R. Tabesh, M. Mahdavi
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引用次数: 12

摘要

物联网(IoT)被认为是未来技术的主要关键领域之一,正受到广泛行业的广泛关注。传感器和设备正在生成大量需要存储和处理的高维异构数据。机器学习涵盖了广泛的人工智能技术,可以从非结构化数据中推断出模式和关系。大数据分析是一种先进的统计和预测分析方法,能够处理eb级甚至更多的数据。本文综述了物联网和机器学习技术在健康、智能电网和供应链管理等领域的应用。对文献进行了回顾,以展示研究人员将面临的未来问题和挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Internet of Everything and Machine Learning Applications: Issues and Challenges
The Internet of Things (IoT) is recognized as one of the major key areas of future technology and is gaining vast attention from an extensive range of industries. The sensors and devices are generating massive amounts of high-dimensional and heterogeneous data that need to be stored and processed. Machine learning encompasses the widespread techniques of artificial intelligence that can deduce patterns and relationships from unstructured data. Big data analytics are advanced statistical and predictive analytic methods which are capable of manipulating data in a range of Exabytes and more. This paper presents a review of the applications of the Internet of Everything and the machine learning techniques in the fields of health, smart electrical grid, and supply chain management. A review of the literature has been conducted to demonstrate the future issues and challenges that researchers will face.
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