학술논문
Energy management for wearable medical devices based on gaining-sharing knowledge algorithm
Original Article
Original Article
Document Type
Academic Journal
Author
Source
Complex & Intelligent Systems. December 2023, Vol. 9 Issue 6, p6797, 15 p.
Subject
Language
English
Abstract
Author(s): Samah Mohamed [sup.1], Hazem A. A. Nomer [sup.1], Retaj Yousri [sup.1], Ali Wagdy Mohamed [sup.2] [sup.3], Ahmed Soltan [sup.4], M. Saeed Darweesh [sup.1] Author Affiliations: (1) https://ror.org/03cg7cp61, grid.440877.8, 0000 [...]
Wearable devices are a growing field of research that can have a wide range of applications. The energy harvester is the most common source of power for wearable devices as well as in wireless sensor networks that require a battery-free operation. However, their power is restricted; consequently, power saving is crucial for wearable devices. Finding the best schedule for the various tasks that run on the wearable device can help to reduce power consumption. This paper presents a task scheduler for wearable medical devices based on Gaining-Sharing Knowledge (GSK) algorithm. The purpose of this task scheduler is to handle the tasks of a heart rate sensor and a temperature sensor to optimize the energy consumption throughout wearable medical devices. The proposed GSK-based scheduling algorithm is assessed against the state-of-the-art technique. The data used in our experiments are collected from an in-lab prototype.
Wearable devices are a growing field of research that can have a wide range of applications. The energy harvester is the most common source of power for wearable devices as well as in wireless sensor networks that require a battery-free operation. However, their power is restricted; consequently, power saving is crucial for wearable devices. Finding the best schedule for the various tasks that run on the wearable device can help to reduce power consumption. This paper presents a task scheduler for wearable medical devices based on Gaining-Sharing Knowledge (GSK) algorithm. The purpose of this task scheduler is to handle the tasks of a heart rate sensor and a temperature sensor to optimize the energy consumption throughout wearable medical devices. The proposed GSK-based scheduling algorithm is assessed against the state-of-the-art technique. The data used in our experiments are collected from an in-lab prototype.