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Inventions 2019, 4(1), 8; https://doi.org/10.3390/inventions4010008

Machine Learning Applications: The Past and Current Research Trend in Diverse Industries

Department of Science and Engineering, Victoria University, Sydney, NSW 2000, Australia
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Received: 22 November 2018 / Revised: 10 January 2019 / Accepted: 28 January 2019 / Published: 3 February 2019
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Abstract

Dramatic changes in the way we collect and process data has facilitated the emergence of a new era by providing customised services and products precisely based on the needs of clients according to processed big data. It is estimated that the number of connected devices to the internet will pass 35 billion by 2020. Further, there has also been a massive escalation in the amount of data collection tools as Internet of Things devices generate data which has big data characteristics known as five V (volume, velocity, variety, variability and value). This article reviews challenges, opportunities and research trends to address the issues related to the data era in three industries including smart cities, healthcare and transportation. All three of these industries could greatly benefit from machine learning and deep learning techniques on big data collected by the Internet of Things, which is named as the internet of everything to emphasise the role of connected devices for data collection. In the smart grid portion of this paper, the recently developed deep reinforcement learning techniques and their applications in Smart Cities are also presented and reviewed. View Full-Text
Keywords: IoT; healthcare; smart cities; smart grid; supply chain management; machine learning IoT; healthcare; smart cities; smart grid; supply chain management; machine learning
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Ameri Sianaki, O.; Yousefi, A.; Tabesh, A.R.; Mahdavi, M. Machine Learning Applications: The Past and Current Research Trend in Diverse Industries. Inventions 2019, 4, 8.

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