[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.9717/kmms.2020.23.3.447

IoT Device Classification According to Context-aware Using Multi-classification Model

Zhang, Xu (School of Computer Science and Engineering, Kyungpook National University)
Ryu, Shinhye (School of Computer Science and Engineering, Kyungpook National University)
Kim, Sangwook (School of Computer Science and Engineering, Kyungpook National University)

Publication Information

Journal of Korea Multimedia Society / v.23, no.3, 2020 , pp. 447-459 More about this Journal

Abstract

The Internet of Things(IoT) paradigm is flourishing strenuously for the last two decades. Researchers around the globe have their dreams to transmute every real-world object to the virtual object. Consequently, IoT devices are escalating exponentially. The abrupt evolution of these IoT devices has caused a major challenge i.e. object classification. In order to classify devices comprehensively and accurately, this paper proposes a context-aware based multi-classification model for devices, which classifies the smart devices according to people's contexts. However, the classification features of contextual data of different contexts are difficult to extract. The deep learning algorithm has the capability to solve this problem. This paper proposes a context-aware based multi-classification model of devices, which classifies the smart devices according to people's contexts.

Keywords

Multi-classification; Internet of Things; Context-aware; Deep Learning;

Citations & Related Records

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