Mining Iot Data for Next Generation Smart Cities
Abhinav Garg1, Manisha Jailia2
1Abhinav Garg, Assistant Professor, NIFT, Hyderabad, India.
2Dr. Manisha Jailia, Associate Professor, Banasthali Vidyapith, Rajasthan , India.
Manuscript received on July 20, 2019. | Revised Manuscript received on August 10, 2019. | Manuscript published on August 30, 2019. | PP: 259-262 | Volume-8 Issue-6, August 2019. | Retrieval Number: E7537068519/2019©BEIESP | DOI: 10.35940/ijeat.E7537.088619
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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: Convergence of Cloud, IoT, Networking devices and Data science has ignited a new era of smart cities concept all around us. The backbone of any smart city is the underlying infrastructure involving thousands of IoT devices connected together to work in real time. Data Analytics can play a crucial role in gaining valuable insights into the volumes of data generated by these devices. The objective of this paper is to apply some most commonly used classification algorithms to a real time dataset and compare their performance on IoT data. The performance summary of the algorithms under test is also tabulated.
Keywords: Classification, Data Mining, IoT (Internet of Things), Smart Cities.