Harvesting energy overview for sustainable wireless sensor networks

Author:

Shokoor Fawad1,Shafik Wasswa2

Affiliation:

1. Computer Engineering Department, Yazd University, Yazd, Iran

2. Dig Connectivity Research Laboratory (DCRLab), Kampala, Uganda

Abstract

Energy harvesting (EH) has emerged as a transformative research paradigm by converting ambient energy into electrical energy for natural and artificial applications. This paper explores the potential of EH in powering autonomous electronic devices facilitated by simplified processes to harness kinetic, solar, thermal, wind, and salinity gradients. Mainly, the focus lies on the applicability of these energy sources to small wireless automatic devices used in wireless sensor networks (WSNs). WSNs consist of cutting-edge sensors spatially distributed to monitor physical conditions and organize collected data at a central network location. Their pervasive existence enables efficient computing through sound resource management, interconnected via the internet and other high-tech innovations. This study evaluates EH developments to minimize resource utilization in WSNs, examining key features, proposed frameworks, and models. Furthermore, it reviews specific energy source productions utilized by WSNs. The feasibility of energy storage is also discussed, highlighting its potential for WSNs and paving the way for future directions in this field.

Publisher

IOS Press

Reference71 articles.

1. Energy-harvesting wireless sensor networks: A review;Adu-Manu;ACM Transactions on Sensor Networks,2020

2. Enhanced zone-based energy aware data collection protocol for wsns;Allam;Journal of King Saud University – Computer and Information Sciences,2019

3. Energy-efficient method for wireless sensor networks low-power radio operation in Internet of things;Amirinasab;Electronics,2020

4. A stochastic game approach for collaborative beam forming in sdn-based energy harvesting wireless sensor networks;Bao;IEEE Internet of Things Journal,2019

5. Extending accurate time distribution and timeliness capabilities over the air to enable future wireless industrial automation systems;Cavalcanti;Proc. IEEE,2019

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3