A method for estimating the location of RFID tags based on deep learning

Abstract

The present invention relates to a deep learning-based RFID tag position estimation method, including a CNN network model training method and a deep learning-based RFID tag position estimation algorithm using method: the CNN network model training method includes: S11, input training data set; S12, Perform data preprocessing; S13, build and train the CNN network model; S14, output the parameters of the CNN network model; the method of using the RFID tag position estimation algorithm based on deep learning includes: S21, input the actual sampling data; S22, input the actual The sampled data is preprocessed; S23, using the network model to estimate the position; S24, using the CNN network model to estimate the position of the RFID tag. The invention can identify the relative position of the RFID tags on the conveyor belt, realize accurate estimation of the sequence of multiple tags, and provide reliable information for automatic sorting.

Description

technical field [0001] The invention relates to the technical field of radio frequency identification, in particular to a method for estimating the position of an RFID tag based on deep learning. Background technique [0002] With the development of the country's social economy, especially the prosperity of the Internet economy in recent years, the modern logistics industry has penetrated into all aspects of people's work, production, and life, and has become a leading industry that guides production and promotes consumption. As the core node in the modern logistics network, the advanced distribution center is equipped with a modern automatic sorting system, which can greatly improve the sorting efficiency and break the cost and error caused by traditional manual sorting. Therefore, the automatic sorting system is a key factor in improving the efficiency of the entire logistics system. [0003] At present, the information of items to be sorted is mainly obtained manually by...

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