Research of Various Data Mining Techniques for IoT Applications
Shaik Johny Basha1, M.V.V.S. Subrahmanyam2
1Shaik Johny Basha, Assistant Professor, Lakireddy Bali Reddy College of Engineering (A), Mylavaram (Andhra Pradesh), India.
2M.V.V.S. Subrahmanyam, Assistant Professor, Sasi Institute of Technology and Engineering (A), Tadepalligudem (Andhra Pradesh), India.
Manuscript received on 13 October 2019 | Revised Manuscript received on 22 October 2019 | Manuscript Published on 02 November 2019 | PP: 1083-1086 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B11850982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1185.0982S1119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In recent years everything is connected and passing through the internet, but Internet of Things (IOT), which will change all aspects of our lives and future. While the things are connected to the internet, they will generate the huge amount of information which has to be processed. The information that gathered from various IoT devices has to be recognized and organized according to the environments of their type. To recognize and organize the data gathered from different things, the important task to be played is making things passing through different Data Mining Techniques (DMT). In this article, we mainly focus on analysis of various Data Mining Techniques over the data that has been generated by the IOT Devices which are connected over the internet using DBSCAN Technique. And also performed review over different Data Mining Techniques for Data Analysis.
Keywords: IoT, Data Mining Techniques (DMT), K-Means Algorithm.
Scope of the Article: IoT