198
5 Optimization Algorithm and RFID System Physical Anti-Collision
reading distance and corresponding distribution is studied via image processing and
SVM. As a result, the reading distance of tags could be predicted according to
the corresponding distribution. Finally, a 3D coordinate measurement system of
RFID multi-tag network based on dual CCD is designed, and the 3D coordinates
of RFID multi-tag network are measured by image method. When the obtained
images are noisy, the wavelet threshold denoising method is used to improve the
quality of the images. After that, the 3D coordinates of RFID multi-tag are obtained
based on the template matching method. The measurement results show that the 3D
coordinate measurement system of RFID multi-tag network is very effective and
useful. Finally, the nonlinear relation model between the 3D coordinates distribution
of RFID multi-tag network and the corresponding reading distance is established
by using wavelet neural network. The paper defines the relative error to evaluate
the predictive performance of neural networks which are discussed in this paper.
Compared with GA-BP neural network and PSO neural network, the wavelet neural
network can better predict the RFID multi-tag network distribution of the reading
distance. The average prediction relative error is 0.71% and the average time cost of
wavelet neural network is 2.17s. The time cost of the wavelet neural network is about
1% of the other two methods. The values of average prediction relative error and the
time cost of the wavelet neural network are very small. Compared with corresponding
method, the proposed method has two advantages.
References
1. Want R (2006) An introduction to RFID technology. Pervasive Comput 5(1):25–33
2. Valero E, Adán A, Cerrada C (2015) Evolution of RFID applications in construction: a literature
review. Sensors 15:15988–16008
3. Yu Y, Yu X, Zhao Z (2016) Measurement uncertainty limit analysis of biased estimators in
RFID multiple tags system. IET Meas Sci Technol 10:449–455
4. Yu Y, Yu X, Zhao Z, Wang D (2017) A novel method to evaluate the dynamic performance of
RFID positioning system. J Comput 28:184–195
5. Li ZH, He CH, Li JM et al (2014) RFID reader anti-collision algorithm using adaptive
hierarchical artificial immune system. Exp Syst Appl 41(5):2126–2133
6. Joo YI, Seo DH, Kim JW (2014) An efficient anti-collision protocol for fast identification of
RFID tags. Wirel Personal Commun 77(1):767–775
7. Myung J, Lee W, Srivastava J (2006) Adaptive binary splitting for efficient RFID tag anticollision. IEEE Commun Lett 10(3):144–146
8. Li BB, Feng XX, Wang CX et al (2012) Multi-passive sensors resource allocation algorithm
based on information gain. Syst Eng Electron 34(3):502–507
9. Gibson R, Atkinson R, Gordon J (2016) A review of underwater stereo-image measurement
for marine biology and ecology applications Oceanogr. Mar Biol 4:7257–7292
10. Ma W, Dong T, Tian H (2014) Line-scan CCD camera calibration in 2D coordinate
measurement. Optik-Int J Light Electron Opt 125:4795–4798
11. Dong T, Hua D, Li Y (2014) Measuring principle of vertical target density based on single
linear array CCD camera. Optik-Int J Light Electron Opt 125:176–178
12. Fahringer TW, Lynch KP, Thurow BS (2015) Volumetric particle image velocimetry with a
single plenoptic camera. Meas Sci Technol 26:115–201
5 Optimization Algorithm and RFID System Physical Anti-Collision
reading distance and corresponding distribution is studied via image processing and
SVM. As a result, the reading distance of tags could be predicted according to
the corresponding distribution. Finally, a 3D coordinate measurement system of
RFID multi-tag network based on dual CCD is designed, and the 3D coordinates
of RFID multi-tag network are measured by image method. When the obtained
images are noisy, the wavelet threshold denoising method is used to improve the
quality of the images. After that, the 3D coordinates of RFID multi-tag are obtained
based on the template matching method. The measurement results show that the 3D
coordinate measurement system of RFID multi-tag network is very effective and
useful. Finally, the nonlinear relation model between the 3D coordinates distribution
of RFID multi-tag network and the corresponding reading distance is established
by using wavelet neural network. The paper defines the relative error to evaluate
the predictive performance of neural networks which are discussed in this paper.
Compared with GA-BP neural network and PSO neural network, the wavelet neural
network can better predict the RFID multi-tag network distribution of the reading
distance. The average prediction relative error is 0.71% and the average time cost of
wavelet neural network is 2.17s. The time cost of the wavelet neural network is about
1% of the other two methods. The values of average prediction relative error and the
time cost of the wavelet neural network are very small. Compared with corresponding
method, the proposed method has two advantages.
References
1. Want R (2006) An introduction to RFID technology. Pervasive Comput 5(1):25–33
2. Valero E, Adán A, Cerrada C (2015) Evolution of RFID applications in construction: a literature
review. Sensors 15:15988–16008
3. Yu Y, Yu X, Zhao Z (2016) Measurement uncertainty limit analysis of biased estimators in
RFID multiple tags system. IET Meas Sci Technol 10:449–455
4. Yu Y, Yu X, Zhao Z, Wang D (2017) A novel method to evaluate the dynamic performance of
RFID positioning system. J Comput 28:184–195
5. Li ZH, He CH, Li JM et al (2014) RFID reader anti-collision algorithm using adaptive
hierarchical artificial immune system. Exp Syst Appl 41(5):2126–2133
6. Joo YI, Seo DH, Kim JW (2014) An efficient anti-collision protocol for fast identification of
RFID tags. Wirel Personal Commun 77(1):767–775
7. Myung J, Lee W, Srivastava J (2006) Adaptive binary splitting for efficient RFID tag anticollision. IEEE Commun Lett 10(3):144–146
8. Li BB, Feng XX, Wang CX et al (2012) Multi-passive sensors resource allocation algorithm
based on information gain. Syst Eng Electron 34(3):502–507
9. Gibson R, Atkinson R, Gordon J (2016) A review of underwater stereo-image measurement
for marine biology and ecology applications Oceanogr. Mar Biol 4:7257–7292
10. Ma W, Dong T, Tian H (2014) Line-scan CCD camera calibration in 2D coordinate
measurement. Optik-Int J Light Electron Opt 125:4795–4798
11. Dong T, Hua D, Li Y (2014) Measuring principle of vertical target density based on single
linear array CCD camera. Optik-Int J Light Electron Opt 125:176–178
12. Fahringer TW, Lynch KP, Thurow BS (2015) Volumetric particle image velocimetry with a
single plenoptic camera. Meas Sci Technol 26:115–201