Towards Always-on Event-based Cameras for Long-lasting Battery-operated Smart Sensor Nodes

Moritz Scherer, Philipp Mayer, Alfio Di Mauro, M. Magno, L. Benini
{"title":"Towards Always-on Event-based Cameras for Long-lasting Battery-operated Smart Sensor Nodes","authors":"Moritz Scherer, Philipp Mayer, Alfio Di Mauro, M. Magno, L. Benini","doi":"10.1109/I2MTC50364.2021.9460037","DOIUrl":null,"url":null,"abstract":"A recent and promising approach to minimize the power consumption of always-on battery-operated sensors is to perform “smart” detection of events to trigger processing. This approach effectively reduces the data bandwidth and power consumption at the system-level and increases the lifetime of sensor nodes. This paper presents an always-on, event-driven ultra-low-power camera platform for motion detection applications. The platform exploits an event-driven VGA imager that features a motion detection mode based on a tunable scene background subtraction algorithm and a grayscale imaging mode. To reduce the power consumption in the motion detection mode, the platform implements a configurable refresh rate which allows for adaption to sensing requirements by trading off between power consumption and detection sensitivity. With accurate experimental evaluation the paper demonstrates that the proposed approach reduces the system-level power consumption for always-on motion sensing applications by switching between an active 15 FPS imaging mode, consuming 5.5 mW and a low-power motion detection mode consuming 1.8 mW. We further estimate the power consumption for a single-chip solution and show that the system-level power budget can be reduced to 2.4 mW in imaging, and $400\\ \\mu\\mathrm{W}$ in detection mode.","PeriodicalId":6772,"journal":{"name":"2021 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","volume":"25 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/I2MTC50364.2021.9460037","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

A recent and promising approach to minimize the power consumption of always-on battery-operated sensors is to perform “smart” detection of events to trigger processing. This approach effectively reduces the data bandwidth and power consumption at the system-level and increases the lifetime of sensor nodes. This paper presents an always-on, event-driven ultra-low-power camera platform for motion detection applications. The platform exploits an event-driven VGA imager that features a motion detection mode based on a tunable scene background subtraction algorithm and a grayscale imaging mode. To reduce the power consumption in the motion detection mode, the platform implements a configurable refresh rate which allows for adaption to sensing requirements by trading off between power consumption and detection sensitivity. With accurate experimental evaluation the paper demonstrates that the proposed approach reduces the system-level power consumption for always-on motion sensing applications by switching between an active 15 FPS imaging mode, consuming 5.5 mW and a low-power motion detection mode consuming 1.8 mW. We further estimate the power consumption for a single-chip solution and show that the system-level power budget can be reduced to 2.4 mW in imaging, and $400\ \mu\mathrm{W}$ in detection mode.
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
用于电池供电的智能传感器节点的永远在线的基于事件的摄像头
最近有一种很有前途的方法,可以最大限度地减少电池供电传感器的功耗,即对事件进行“智能”检测以触发处理。该方法有效地降低了系统级的数据带宽和功耗,提高了传感器节点的寿命。本文提出了一种用于运动检测应用的始终在线、事件驱动的超低功耗相机平台。该平台利用事件驱动的VGA成像仪,该成像仪具有基于可调场景背景减法算法的运动检测模式和灰度成像模式。为了降低运动检测模式下的功耗,该平台实现了一个可配置的刷新率,允许通过在功耗和检测灵敏度之间进行权衡来适应传感要求。通过精确的实验评估,本文证明了该方法通过在主动15 FPS成像模式(消耗5.5 mW)和低功耗运动检测模式(消耗1.8 mW)之间切换,降低了始终在线的运动传感应用的系统级功耗。我们进一步估算了单芯片解决方案的功耗,并表明在成像模式下系统级功耗预算可降至2.4 mW,在检测模式下可降至400 $ \ \mu\math {W}$。
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
Microwave Quantification of Porosity Level in 3D Printed Polymers Fast Transient Harmonic Selective Extraction Based on Modulation-CDSC-SDFT A UWB-based localization system: analysis of the effect of anchor positions and robustness enhancement in indoor environments Miniaturised bidirectional acoustic tag to enhance marine animal tracking studies Overload Current Interruption Protection Method based on Tunnel Magnetoresistive Sensor Measurement
×
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