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Energy Harvesting Based Body Area Networks for Smart Health.
Hao, Yixue; Peng, Limei; Lu, Huimin; Hassan, Mohammad Mehedi; Alamri, Atif.
Afiliação
  • Hao Y; School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China. yixuehao@hust.edu.cn.
  • Peng L; Department of Industrial and Information System Engineering, Ajou University, Suwon 443749 , Korea. auroraplm@ajou.ac.kr.
  • Lu H; Department of Mechanical and Control Engineering, Kyushu Institute of Technology, Fukuoka prefecture 8048550, Japan. luhuimin@ieee.org.
  • Hassan MM; College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia. mmhassan@ksu.edu.sa.
  • Alamri A; College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia. atif@ksu.edu.sa.
Sensors (Basel) ; 17(7)2017 Jul 10.
Article em En | MEDLINE | ID: mdl-28698501
ABSTRACT
Body area networks (BANs) are configured with a great number of ultra-low power consumption wearable devices, which constantly monitor physiological signals of the human body and thus realize intelligent monitoring. However, the collection and transfer of human body signals consume energy, and considering the comfort demand of wearable devices, both the size and the capacity of a wearable device's battery are limited. Thus, minimizing the energy consumption of wearable devices and optimizing the BAN energy efficiency is still a challenging problem. Therefore, in this paper, we propose an energy harvesting-based BAN for smart health and discuss an optimal resource allocation scheme to improve BAN energy efficiency. Specifically, firstly, considering energy harvesting in a BAN and the time limits of human body signal transfer, we formulate the energy efficiency optimization problem of time division for wireless energy transfer and wireless information transfer. Secondly, we convert the optimization problem into a convex optimization problem under a linear constraint and propose a closed-form solution to the problem. Finally, simulation results proved that when the size of data acquired by the wearable devices is small, the proportion of energy consumed by the circuit and signal acquisition of the wearable devices is big, and when the size of data acquired by the wearable devices is big, the energy consumed by the signal transfer of the wearable device is decisive.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2017 Tipo de documento: Article