Role of Data Mining in Developing a Smart Iot and its Challenges
Nandhini.S1, Jeen Marseline. K.S2, Deepa.B3
1Nandhini.S, Assistant Professor, Department of Computer Technology, Sri Krishna Arts and Science College, Coimbatore (Tamil Nadu), India.
2Jeen Marseline. K.S, Assistant Professor, Department of Information Technology, Sri Krishna Arts and Science College Coimbatore (Tamil Nadu), India.
3Deepa.B, Assistant Professor, Department of Information Technology, Sri Krishna Arts and Science College, Coimbatore (Tamil Nadu), India.
Manuscript received on 05 May 2019 | Revised Manuscript received on 17 May 2019 | Manuscript Published on 23 May 2019 | PP: 544-546 | Volume-7 Issue-6S5 April 2019 | Retrieval Number: F10950476S519/2019©BEIESP
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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: Internet of Things (IoT) is a rapidly growing technology on which enterprises are building their future. IoT will change everything into “smart” ranging from smart home to smart government. To make them smart the various IoT devices are used which act as sensors and generate vast amount of data. The right IoT technology will aggregate, process and interpret the data generated by smart devices. The process of information extraction from a very large database is difficult. To make the data useful, which is collected from, a variety of devices, it is appropriate to use data mining techniques. Using various data mining techniques, we can extract data from various sources in an effective manner. This paper gives an overview of different data mining techniques, which can make IoT devices smarter and also addresses some challenges faced in applying these techniques.
Keywords: IoT, Data Mining, Classification, Logistics Regression, Naïve Bayes, K- Nearest Neighbors.
Scope of the Article: Data Mining