Kinetic-based micro energy-harvesting for wearable sensors

D. Budic, D. Simunic, K. Sayrafian-Pour
{"title":"Kinetic-based micro energy-harvesting for wearable sensors","authors":"D. Budic, D. Simunic, K. Sayrafian-Pour","doi":"10.1109/COGINFOCOM.2015.7390645","DOIUrl":null,"url":null,"abstract":"Wearable sensors are considered to be a key component of cognitive infocommunications systems. These sensors, which are basically enabler of inter-cognitive communication, will provide physical interfaces between humans and future information and communication technology (ICT) devices. Due to their small size, such sensors are often powered by small batteries which might necessitate frequent recharge or even sensor replacement. Energy harvesting can reduce the charging frequency of these sensors. Longer operational lifetime can simplify the everyday use of wearable sensors in many of their applications. In this paper, our objective is to estimate the average amount of kinetic energy that can be harvested to power a wearable device. To obtain this estimate, we have measured typical acceleration of the human body through the use of a triaxial accelerometer placed at various locations on the body surface. These locations are assumed to be associated with the typical placement of a wearable sensor. Using the mathematical model of a micro energy-harvester, instantaneous harvested power can be generated, and target statistics such as average power can be calculated. Our preliminary results show that kinetic-based micro harvesters could be a promising technology for prolonging the operational lifetime of wearable sensors.","PeriodicalId":377891,"journal":{"name":"2015 6th IEEE International Conference on Cognitive Infocommunications (CogInfoCom)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 6th IEEE International Conference on Cognitive Infocommunications (CogInfoCom)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COGINFOCOM.2015.7390645","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

Wearable sensors are considered to be a key component of cognitive infocommunications systems. These sensors, which are basically enabler of inter-cognitive communication, will provide physical interfaces between humans and future information and communication technology (ICT) devices. Due to their small size, such sensors are often powered by small batteries which might necessitate frequent recharge or even sensor replacement. Energy harvesting can reduce the charging frequency of these sensors. Longer operational lifetime can simplify the everyday use of wearable sensors in many of their applications. In this paper, our objective is to estimate the average amount of kinetic energy that can be harvested to power a wearable device. To obtain this estimate, we have measured typical acceleration of the human body through the use of a triaxial accelerometer placed at various locations on the body surface. These locations are assumed to be associated with the typical placement of a wearable sensor. Using the mathematical model of a micro energy-harvester, instantaneous harvested power can be generated, and target statistics such as average power can be calculated. Our preliminary results show that kinetic-based micro harvesters could be a promising technology for prolonging the operational lifetime of wearable sensors.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于动力学的可穿戴传感器微能量收集
可穿戴传感器被认为是认知信息通信系统的关键组成部分。这些传感器基本上是认知间通信的推动者,将提供人类与未来信息和通信技术(ICT)设备之间的物理接口。由于尺寸小,这些传感器通常由小电池供电,这可能需要经常充电甚至更换传感器。能量收集可以降低这些传感器的充电频率。更长的使用寿命可以简化可穿戴传感器在许多应用中的日常使用。在本文中,我们的目标是估计可收集的动能的平均量,为可穿戴设备提供动力。为了得到这个估计,我们通过使用放置在身体表面不同位置的三轴加速度计来测量人体的典型加速度。假设这些位置与可穿戴传感器的典型放置位置相关。利用微型能量采集器的数学模型,可以产生瞬时收获功率,并计算平均功率等目标统计数据。我们的初步结果表明,基于动力学的微型收割机可能是一种很有前途的技术,可以延长可穿戴传感器的使用寿命。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Brain activity measured with fNIRS for the prediction of cognitive workload Towards computer-assisted language learning with robots, wikipedia and CogInfoCom A motivational model of hunger for a cognitive architecture Distributed processing of biological interactions using Hadoop Mobile applications for traffic safety
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1