Internet of Everything and Machine Learning Applications: Issues and Challenges

被引:5
|
作者
Sianaki, Omid Ameri [1 ]
Yousefi, Ashkan [2 ]
Tabesh, Azadeh Rajabian [3 ]
Mahdavi, Mehregan [1 ]
机构
[1] Victoria Univ, Dept Sci & Engn, Sydney, NSW, Australia
[2] Univ Calif Berkeley, IEOR, Berkeley, CA USA
[3] Curtin Univ, Sch Mkt, Perth, WA, Australia
关键词
Internet of Everything; machine learning; eHealth; smart grid; supply chain management; SUPPLY CHAIN MANAGEMENT; THINGS; MODEL;
D O I
10.1109/WAINA.2018.00171
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:704 / 708
页数:5
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