COMPASS: Community Optimized Measuring of Positions Associated with Sensing Singnals
碩士 === 國立陽明大學 === 醫學工程研究所 === 97 === In this paper we present COMPASS (Community-Optimized Measuring of Positions Associated with Sensing Signals), a method to improve indoor location sensing accuracy using Radio Frequency Identification (RFID), based on the design using reference tags. The major ad...
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ndltd-TW-097YM0055300192016-05-04T04:16:31Z http://ndltd.ncl.edu.tw/handle/43106135019665257218 COMPASS: Community Optimized Measuring of Positions Associated with Sensing Singnals 以社區分群概念來最佳化訊號之室內定位系統 Chu-Seng, Cheng 鄭竹昇 碩士 國立陽明大學 醫學工程研究所 97 In this paper we present COMPASS (Community-Optimized Measuring of Positions Associated with Sensing Signals), a method to improve indoor location sensing accuracy using Radio Frequency Identification (RFID), based on the design using reference tags. The major advantage of COMPASS is that it provides more accuracy location, compared with LANDMARC, and keeps the beauty of true simplicity, giving it the ability to track down moving object in real-time environment. Yet, based on our result, we do see that while improving the average accuracy, some measurements turn out having a larger error, making a bigger maximum error of the algorithm. We find out ways to improve and predict large error observations, forming two types of hybrid systems, one with a dynamic community size and the other with LANDMARC. Both systems succeed a better average positioning accuracy and less maximum error compared with the original COMPASS system. Finally, we point out suggestions for further research and future work. Wei-Chyn Chu 朱唯勤 2009 學位論文 ; thesis 56 en_US |
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碩士 === 國立陽明大學 === 醫學工程研究所 === 97 === In this paper we present COMPASS (Community-Optimized Measuring of
Positions Associated with Sensing Signals), a method to improve indoor location
sensing accuracy using Radio Frequency Identification (RFID), based on the design
using reference tags. The major advantage of COMPASS is that it provides more
accuracy location, compared with LANDMARC, and keeps the beauty of true
simplicity, giving it the ability to track down moving object in real-time environment.
Yet, based on our result, we do see that while improving the average accuracy,
some measurements turn out having a larger error, making a bigger maximum error of
the algorithm. We find out ways to improve and predict large error observations,
forming two types of hybrid systems, one with a dynamic community size and the
other with LANDMARC. Both systems succeed a better average positioning accuracy
and less maximum error compared with the original COMPASS system.
Finally, we point out suggestions for further research and future work.
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author2 |
Wei-Chyn Chu |
author_facet |
Wei-Chyn Chu Chu-Seng, Cheng 鄭竹昇 |
author |
Chu-Seng, Cheng 鄭竹昇 |
spellingShingle |
Chu-Seng, Cheng 鄭竹昇 COMPASS: Community Optimized Measuring of Positions Associated with Sensing Singnals |
author_sort |
Chu-Seng, Cheng |
title |
COMPASS: Community Optimized Measuring of Positions Associated with Sensing Singnals |
title_short |
COMPASS: Community Optimized Measuring of Positions Associated with Sensing Singnals |
title_full |
COMPASS: Community Optimized Measuring of Positions Associated with Sensing Singnals |
title_fullStr |
COMPASS: Community Optimized Measuring of Positions Associated with Sensing Singnals |
title_full_unstemmed |
COMPASS: Community Optimized Measuring of Positions Associated with Sensing Singnals |
title_sort |
compass: community optimized measuring of positions associated with sensing singnals |
publishDate |
2009 |
url |
http://ndltd.ncl.edu.tw/handle/43106135019665257218 |
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