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IoT Data Classifications for Smart Home Deployment

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Abstract

Gadgets installed in smart home ease human life and can be controlled from remote locations. These gadgets are sensor-based and generate different types of data. These data need to be processed faster to provide a quick response in a smart home application. Edge nodes dwell at the edges of IoT gadgets for faster processing of data. In this paper, we have used a data classifier strategy to overcome a few existing issues in smart home applications. Certain rules are derived based on which the proposed classifier classify the data. Then, data are forwarded to edge nodes for processing. The performance of a proposed data classifier is studied using different parameters. From the simulation study, it is found that the proposed strategy gives better results in terms of average execution time, service latency and resource utilization.

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Acknowledgements

The initial version of this article has been accepted for presentation in \(7\mathrm{th}\) IEEE International Symposium on Smart Electronic Systems, 2021 [31].

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  1. School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, India

    Ashish Virendra Chandak & Niranjan K. Ray

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  1. Ashish Virendra Chandak
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Correspondence to Ashish Virendra Chandak.

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Chandak, A.V., Ray, N.K. IoT Data Classifications for Smart Home Deployment. SN COMPUT. SCI. 3, 95 (2022). https://doi.org/10.1007/s42979-021-00979-w

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