Techniques, Models and Challenges of Data Mining in Internet of Things (IOT)
M Chandra Prabha1, R Viswanathan2
1JM ChandraPrabha, , Research Scholar, Galgotias University, Greater Noida, U.P, India.
2Dr R Viswanathan, Associate Professor, Galgotias University, Greater Noida, U.P, India.

Manuscript received on November 20, 2019. | Revised Manuscript received on November 28, 2019. | Manuscript published on 30 November, 2019. | PP: 7077-7080 | Volume-8 Issue-4, November 2019. | Retrieval Number: D5238118419/2019©BEIESP | DOI: 10.35940/ijrte.D5238.118419

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Abstract: Due to many achievements in the field of communication and sensor networks, Internet of Things becomes an emerging technology which makes the human life easier and comfortable. This technology development paves the way to work and live in a comfortable manner. In internet, interfacing of any object is very difficult, but IoT makes the process very easier that too in a short span of time. In IoT, a huge of amount of data has been captured that is considered as huge business and social value data’s’. So, IoT needs a model which is used to extract those high business data. Thus, data mining is a process which extracts high business data from huge amount of data easily. In this paper, a systematic review has been carried out on various data mining techniques and models that have been applied in IoT. Also its advantages and disadvantages have been discussed along with the challenges and future trends of IoT..
Keywords: Internet of Things, Data Mining, Data Mining techniques, Data Mining Models, Challenges.
Scope of the Article:  Data Mining.