A Method to Enhance Tag Identification Efficiency Based on Tail Code Optimization Feature Sets

Xiaowu Li, Wei Cui, Runxin Li, Lianyin Jia, Jinguo You

Abstract: Radio Frequency Identification (RFID) is crucial for the Internet of Things, with a key challenge being the efficient prevention of tag collisions for quick identification. This paper presents a novel approach for rapid tag recognition in small to medium-sized warehouses, combining a tag optimization feature set with a tail code recognition mechanism. To minimize the frequency of scanning for duplicate tags and reduce the occurrence of collisions, we construct an optimization feature set based on the reader's position. This set helps in assessing the likelihood of tag repetition through its linear variation. It also incorporates a tail code mechanism that recognizes only the last 22 digits of the tag's EPC code, significantly speeding up identification. The tail code length is dynamically adjusted based on the number of tags to maintain uniqueness. Simulation results indicate that our approach significantly reduces the identification of duplicate tags and minimizes the instances of collisions.

External IDs:dblp:journals/ieiceta/LiCLJY24