TY - GEN
T1 - Prediction of RFID tag detection for a stationary carton box
AU - Jo, Minho
AU - Cha, Si Ho
AU - Choo, Hyunseung
AU - Chen, Hsiao Hwa
PY - 2008
Y1 - 2008
N2 - Passive RFID Tag detection (or recognition) is one of the most important issues for the RFID systems to be successfully deployed in various applications. Passive RFID tag position greatly influences RFID tag detection by the RFID reader antenna. In this paper, we propose a method for a carton box object on a wooden pallet by an experimental approach based on tag signal strength, and propose a method for predicting detection directly related to the strength of tag signal using an intelligent machine learning technique called support vector machine. The proposed intelligent method is capable of saving time and costs by quick prediction of tag detection. Experiment shows that the proposed approach predicts tag recognition for a carton box object as accurately as around 95% for various reader heights and read field length values. The proposed approach is effective for determining the best tag detection influence factor condition on the target object by using the predicted detectability.
AB - Passive RFID Tag detection (or recognition) is one of the most important issues for the RFID systems to be successfully deployed in various applications. Passive RFID tag position greatly influences RFID tag detection by the RFID reader antenna. In this paper, we propose a method for a carton box object on a wooden pallet by an experimental approach based on tag signal strength, and propose a method for predicting detection directly related to the strength of tag signal using an intelligent machine learning technique called support vector machine. The proposed intelligent method is capable of saving time and costs by quick prediction of tag detection. Experiment shows that the proposed approach predicts tag recognition for a carton box object as accurately as around 95% for various reader heights and read field length values. The proposed approach is effective for determining the best tag detection influence factor condition on the target object by using the predicted detectability.
UR - https://www.scopus.com/pages/publications/63049135438
U2 - 10.1109/ICSENST.2008.4757107
DO - 10.1109/ICSENST.2008.4757107
M3 - Conference contribution
AN - SCOPUS:63049135438
SN - 9781424421770
T3 - Proceedings of the 3rd International Conference on Sensing Technology, ICST 2008
SP - 248
EP - 253
BT - Proceedings of the 3rd International Conference on Sensing Technology, ICST 2008
T2 - 3rd International Conference on Sensing Technology, ICST 2008
Y2 - 30 November 2008 through 3 December 2008
ER -