An Image Processing and Laser Ranging Approach for Radio Frequency Identification (RFID) Tag Group Reading Performance Prediction

With the large-scale application of radio frequency identification (RFID) tags in warehousing and logistics, it becomes crucial to study the factors that affect the reading performance of RFID tags. To address this issue this paper builds an experimental testing system to deeply study the influence of tag position distribution on the tags' reading performance; however, in tag position measurement process, due to the complex electromagnetic interference in the dynamic state, normal tag position measurement by using antenna may cause errors or even mistakes. So in this paper the image processing non-contact method is adopted to replace the antenna to realize tags' position measurement. After that, the newly emerged deep neural network (DNN) is developed to deeply explore the complex nonlinear relationship existing between the tag position distribution and corresponding reading distance. The established DNN is used to predict the reading distance of tag group. By analysing the predicted reading distance, we may find the optimal three-dimensional (3-D) position distribution corresponding to the maximum reading distance. The method proposed in this paper can be used to guide the position distribution of tags in practical scenarios and thus improve the reading performance of RFID system.