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Influence of Internet of Things (IoT) In Association of Data Mining Towards the Development Smart Cities-A Review Analysis.

Authors :
Priyanka, E. B.
Thangavel, S.
Source :
Journal of Engineering Science & Technology Review. 2020, Vol. 13 Issue 4, p1-21. 21p.
Publication Year :
2020

Abstract

The modern wireless sensor network is focused on integrating the emerging technology of IoT with the real world for enhanced data processing to improve automation and communication more smartly and safely. In the present industrial upgradation with IoT application greatly proved its positive influences on the operation and management phases along with progressive adoption of cloud computing and big data analytics. In Industry, smart monitoring and distributed control of entire architecture are hold up with the renovated technology of the Internet of Things (IoT). It lies on the top layer of the wireless communication network to afford enhanced connectivity among smart wireless or wired sensor with the embedded modern controller to the cloud server. In IoT application, real-time data acquisition is done securely and transmitted to the data analytics services to identify any catastrophic situation existence. It is reliable and moved industrial automation to the next step evolution of formulating to make proactive decisions to decide and react to the industrial variation constraints. Though modernization has shifted to analog to the digital generation, it is interoperable with available protocols and data standardizations in industrial sectors. Hence this paper enumerates the detailed configurations and features of IoT application involved in the modern communication platform towards the development of smart cities by incorporating data mining using AI (Artificial Intelligence). Further, the trending overview of Industrial IoT application in risk-based environments with complete knowledge-based architecture with incorporated wireless technology and protocols are outlined. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17912377
Volume :
13
Issue :
4
Database :
Academic Search Index
Journal :
Journal of Engineering Science & Technology Review
Publication Type :
Academic Journal
Accession number :
146329176
Full Text :
https://doi.org/10.25103/jestr.134.01