Towards convergence of AI and IoT for energy efficient communication in smart homes

Sodhro, A. H., Gurtov, A., Zahid, N., Pirbhulal, S., Wang, L., Rahman, M. M. U., Imran, M. A. and Abbasi, Q. H. (2021) Towards convergence of AI and IoT for energy efficient communication in smart homes. IEEE Internet of Things Journal, 8(12), pp. 9664-9671. (doi: 10.1109/JIOT.2020.3023667)

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Abstract

The convergence of Artificial Intelligence (AI) and Internet of Things (IoT) promotes the energy efficient communication in smart homes. Quality of Service (QoS) optimization during video streaming through wireless micro medical devices (WMMD) in smart healthcare homes is the main purpose of this research. This paper contributes in four distinct ways. First, to propose a novel Lazy Video Transmission Algorithm (LVTA). Second, a novel Video Transmission Rate Control Algorithm (VTRCA) is proposed. Third, a novel cloud-based video transmission framework is developed. Fourth, the relationship between buffer size and performance indicators i.e., peak-to-mean ratio (PMR), energy (i.e., encoding and transmission) and standard deviation is investigated while comparing the LVTA, VTRCA, and Baseline approaches. Experimental results demonstrate that the reduction in encoding (32%, 35.4%) and transmission (37%, 39%) energy drains, PMR (5, 4), and standard deviation (3dB, 4dB) for VTRCA and LVTA, respectively, is greater than that obtained by Baseline during video streaming through WMMD.

Item Type:Articles
Additional Information:This work is also supported by CENIIT project 17.01, Computer and Information Science department, Linkop- ing University, Linkoping, Sweden and in part by CAS President’s International Fellowship Initiative Project (2020VBC0002) China.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Abbasi, Professor Qammer and Imran, Professor Muhammad
Authors: Sodhro, A. H., Gurtov, A., Zahid, N., Pirbhulal, S., Wang, L., Rahman, M. M. U., Imran, M. A., and Abbasi, Q. H.
College/School:College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
College of Science and Engineering > School of Engineering > Systems Power and Energy
Journal Name:IEEE Internet of Things Journal
Publisher:IEEE
ISSN:2327-4662
ISSN (Online):2327-4662
Published Online:14 September 2020
Copyright Holders:Copyright © 2020 IEEE
First Published:First published in IEEE Internet of Things 8(12): 9664-9671
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher

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