Decentralized Energy Efficient Model for Data Transmission in IoT-based Healthcare System

Ali Hassan Sodhro, Mabrook S. Al-Rakhami, Lei Wang, Hina Magsi, Noman Zahid, Sandeep Pirbhulal, K. Nisar, Awais Ahmad
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引用次数: 17

Abstract

The growing world population is facing challenges such as increased chronic diseases and medical expenses. Integrate the latest modern technology into healthcare system can diminish these issues. Internet of medical things (IoMT) is the vision to provide the better healthcare system. The IoMT comprises of different sensor nodes connected together. The IoMT system incorporated with medical devices (sensors) for given the healthcare facilities to the patient and physician can have capability to monitor the patients very efficiently. The main challenge for IoMT is the energy consumption, battery charge consumption and limited battery lifetime in sensor based medical devices. During charging the charges that are stored in battery and these charges are not fully utilized due to non-linearity of discharging process. The short time period needed to restore these unused charges is referred as recovery effect. An algorithm exploiting recovery effect to extend the battery lifetime that leads to low consumption of energy. This paper provides the proposed adaptive Energy efficient (EEA) algorithm that adopts this effect for enhancing energy efficiency, battery lifetime and throughput. The results have been simulated on MATLAB by considering the Li-ion battery. The proposed adaptive Energy efficient (EEA) algorithm is also compared with other state of the art existing method named, BRLE. The Proposed algorithm increased the lifetime of battery, energy consumption and provides the improved performance as compared to BRLE algorithm. It consumes low energy and supports continuous connectivity of devices without any loss/ interruptions.
基于物联网的医疗保健系统数据传输的分散节能模型
不断增长的世界人口正面临着慢性病和医疗费用增加等挑战。将最新的现代技术集成到医疗保健系统中可以减少这些问题。医疗物联网(IoMT)是提供更好的医疗保健系统的愿景。IoMT由连接在一起的不同传感器节点组成。与医疗设备(传感器)相结合的IoMT系统可以将医疗设施提供给患者和医生,可以非常有效地监测患者。IoMT面临的主要挑战是基于传感器的医疗设备的能量消耗、电池充电消耗和有限的电池寿命。在充电过程中,由于放电过程的非线性,存储在电池中的电荷没有得到充分利用。恢复这些未使用的费用所需的短时间被称为恢复效果。一种利用恢复效应延长电池寿命的算法,从而降低能耗。本文提出的自适应能效(EEA)算法利用这种效应来提高能效、电池寿命和吞吐量。并以锂离子电池为例,在MATLAB上进行了仿真。提出的自适应能效(EEA)算法还与其他最先进的现有方法BRLE进行了比较。与BRLE算法相比,该算法提高了电池寿命和能耗,并提供了更高的性能。它消耗低能量,支持设备的连续连接,没有任何丢失/中断。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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