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  4. Sensor-Enhanced Mobility Prediction for Energy-Efficient Localization Energy-Efficient Localization
 
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Sensor-Enhanced Mobility Prediction for Energy-Efficient Localization Energy-Efficient Localization

Resource
IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON 2006), Reston VA, USA
Journal
IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON 2006)
Pages
566-574
Date Issued
2006
Date
2006
Author(s)
You, Chuang-Wen  
Chen, Yi-Chao
Chiang, Ji-Rung
Huang, Polly  
Chu, Hao-Hua
Lau, Seng-Yong
DOI
20060927122839101792
URI
http://scholars.lib.ntu.edu.tw/handle/123456789/325578
http://ntur.lib.ntu.edu.tw/bitstream/246246/20060927122839101792/1/secon2006.pdf
Abstract
Energy efficiency & positional accuracy are often contradictive goals. We propose to decrease power consumption without sacrificing significant accuracy by developing an en-ergy-aware localization that adapts the sampling rate to target's mobility level. In this paper, an energy-aware adaptive localiza-tion system based on signal strength fingerprinting is designed, implemented, & evaluated. Promising to satisfy an application's requirements on positional accuracy, our system tries to adapt its sampling rate to reduce its energy consumption. The contribution of this paper is three-fold. (1) We have developed a model to pre-dict the positional error of a real working positioning engine un-der different mobility levels of mobile targets, estimation error from the positioning engine, processing & networking delay in the location infrastructure, & sampling rate of location infor-mation. (2) In a real test environment, our energy-saving method solves the mobility estimation error problem by utilizing addi-tional sensors on mobile targets. The result is that we can improve the prediction accuracy by as much as 37.01%. (3) We imple-mented our energy-saving methods inside a working localization infrastructure & conducted performance evaluation in a real office environment. Our performance results show as much as 49.76 % reduction in power consumption.
Subjects
Position measurement
Power demand
Quality assurance
SDGs

[SDGs]SDG7

Publisher
臺北市:國立臺灣大學資訊工程學系
Description
Reston VA, USA
Type
conference paper
File(s)
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secon2006.pdf

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224.78 KB

Format

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(MD5):6b87eb8db78dbbed622f695bc5326013

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