DocumentCode
1501974
Title
Intelligent RFID tag detection using support vector machine
Author
Jo, Minho ; Youn, Hee Yong ; Chen, Hsiao-Hwa
Author_Institution
Grad. Sch. of Inf. Manage. & Security, Korea Univ., Seoul, South Korea
Volume
8
Issue
10
fYear
2009
fDate
10/1/2009 12:00:00 AM
Firstpage
5050
Lastpage
5059
Abstract
RFID Tag detection/recognition is one of the most critical issues for successful deployment of RFID systems in diverse applications. The main factors influencing tag detection by RFID reader antenna include tag position, relative position of reader, read field length, etc. In this paper, we analyze the characteristics of tag detection for a carton box object on a wooden pallet by an experimental approach based on tag signal strength, and we propose a method for predicting detection related directly to the strength of tag signal using an intelligent machine learning technique called support vector machine (SVM). The use of the proposed method is able to save time and cost by quick prediction of tag detection. Extensive experiments showed that the proposed approach can predict tag recognition for a carton box object with an accuracy at 95% for various reader heights and read field lengths. The proposed approach is effective for determining the best tag detection influencing factor conditioned on the target object with the help of detectability prediction.
Keywords
radiofrequency identification; signal detection; support vector machines; RFID reader antenna; RFID tag detection; carton box object; radiofrequency identification; signal detection; support vector machines; tag position; Data mining; Learning systems; Machine intelligence; Middleware; Object detection; RFID tags; Radio frequency; Radiofrequency identification; Signal analysis; Support vector machines; RFID, SVM, intelligent prediction of tag detection influencing factor;
fLanguage
English
Journal_Title
Wireless Communications, IEEE Transactions on
Publisher
ieee
ISSN
1536-1276
Type
jour
DOI
10.1109/TWC.2009.071198
Filename
5288941
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