Power consumption analysis of a wireless 1K-pixel visual sensor node: to compress or not?

Geert Braeckman, R. Kleihorst, Jan Hanca, A. Munteanu
{"title":"Power consumption analysis of a wireless 1K-pixel visual sensor node: to compress or not?","authors":"Geert Braeckman, R. Kleihorst, Jan Hanca, A. Munteanu","doi":"10.1145/2789116.2789129","DOIUrl":null,"url":null,"abstract":"The applicability of wireless sensor networks is usually limited by the lifetime of sensor nodes having a restricted energy supply. In case of visual sensors, the amount of collected data increases significantly, resulting in a high power consumption by the transmitter. Efficient video compression algorithms reduce the amount of data which has to be sent. On the other hand, video codecs are known to be computationally demanding. It is unclear whether or not spending more power on compression and less on transmission increases battery lifetime, especially if processing is performed on a general-purpose reprogrammable microcontroller. This paper presents the power profile of a very low-resolution wireless visual sensor node. The node executing a predictive video coding engine is compared against the system transmitting raw data. Both setups are examined while capturing static and dynamic video content in strictly controlled environment conditions. Experimental results prove that video compression executed on the microcontroller prior to the wireless transmission reduces the power consumption of the sensor mote.","PeriodicalId":113163,"journal":{"name":"Proceedings of the 9th International Conference on Distributed Smart Cameras","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 9th International Conference on Distributed Smart Cameras","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2789116.2789129","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

The applicability of wireless sensor networks is usually limited by the lifetime of sensor nodes having a restricted energy supply. In case of visual sensors, the amount of collected data increases significantly, resulting in a high power consumption by the transmitter. Efficient video compression algorithms reduce the amount of data which has to be sent. On the other hand, video codecs are known to be computationally demanding. It is unclear whether or not spending more power on compression and less on transmission increases battery lifetime, especially if processing is performed on a general-purpose reprogrammable microcontroller. This paper presents the power profile of a very low-resolution wireless visual sensor node. The node executing a predictive video coding engine is compared against the system transmitting raw data. Both setups are examined while capturing static and dynamic video content in strictly controlled environment conditions. Experimental results prove that video compression executed on the microcontroller prior to the wireless transmission reduces the power consumption of the sensor mote.
无线1k像素视觉传感器节点的功耗分析:压缩还是不压缩?
无线传感器网络的适用性通常受到能量供应受限的传感器节点寿命的限制。对于视觉传感器,收集的数据量会显著增加,导致发射器的功耗很高。高效的视频压缩算法减少了需要发送的数据量。另一方面,视频编解码器的计算要求很高。目前还不清楚在压缩和传输上花费更多的能量是否会增加电池寿命,特别是如果处理是在通用可编程微控制器上进行的。本文介绍了一种极低分辨率无线视觉传感器节点的功率分布。将执行预测视频编码引擎的节点与传输原始数据的系统进行比较。在严格控制的环境条件下捕获静态和动态视频内容时,对这两种设置进行了检查。实验结果表明,在无线传输之前在单片机上进行视频压缩,降低了传感器的功耗。
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信