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Assessment on Different Classification Algorithms Used in Internet of Things Applications

Assessment on Different Classification Algorithms Used in Internet of Things Applications
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Author(s): Akhil Bansal (University Institute of Technology, RGPV, Bhopal, India), Manish Kumar Ahirwar (University Institute of Technology, RGPV, Bhopal, India) and Piyush K. Shukla (University Institute of Technology, RGPV, Bhopal, India)
Copyright: 2019
Volume: 9
Issue: 1
Pages: 11
Source title: International Journal of Organizational and Collective Intelligence (IJOCI)
Editor(s)-in-Chief: Victor Chang (Teesside University, UK)
DOI: 10.4018/IJOCI.2019010101

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Abstract

The past few years have witnessed the Internet of Things (IoT) has evolved a lot and continues to evolve in various fields such as healthcare, agriculture, smart city, education, industries, automation, home care, etc. This advancement is caused by the development of sensor-enabled devices called IoT devices. The data collected from such devices will be used to identify and manage complex environment around us that will reduce the human intervention and also escalate efficiency, productivity, accuracy and economic benefits of the devices. In this survey article, the authors analyze how the datasets of different applications of the IoT such as agriculture, healthcare, smart city are processed and classified. The article also outlines the recent review of more common classification algorithms such as Support Vector Machine, Naïve Byes, Decision Tree, etc., that were used to classify the dataset with different parameters applied to the Internet of Things applications. In addition, this article also gives a brief review of the applications of the Internet of Things.

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