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An Efficient Early-breaking-estimation and Tree-splitting Missing RFID Tag Identification Protocol.

Mingqiu Fan¹, Lijuan Zhang¹, Lei Lei¹

¹College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.

Sensors (Basel, Switzerland)

|December 9, 2023

Summary

This study introduces an efficient protocol for identifying missing RFID tags in large retail inventories, even with unknown tags present. The new method reduces processing time and improves accuracy, enhancing inventory management reliability.

Keywords:

IoT RFID missing tag identification tag number estimation tree-splitting unknown tag

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Area of Science:

Computer Science
Electrical Engineering
Operations Research

Background:

Retail inventory management faces significant losses from missing items.
Existing RFID tag identification methods struggle with unknown tags, impacting reliability.
Accurate missing tag identification is crucial for efficient large-scale inventory systems.

Purpose of the Study:

To propose an efficient protocol for identifying missing RFID tags in large-scale systems.
To address the challenge of unknown tags interfering with missing tag identification.
To improve the reliability and efficiency of inventory management systems.

Main Methods:

Developed an efficient early-breaking-estimation and tree-splitting-based missing tag identification (ETMTI) protocol.
Implemented early-breaking-estimation and deactivation to handle unknown tags.
Utilized a B-ary splitting tree and bit-tracking for rapid identification and reduced processing time.

Main Results:

The ETMTI protocol significantly outperforms benchmark methods in simulations.
Achieved a shorter processing time for missing tag identification.
Demonstrated a lower false negative rate, improving system accuracy.

Conclusions:

The proposed ETMTI protocol offers an efficient and reliable solution for missing tag identification in large-scale RFID systems.
Effectively handles unknown tags, a common challenge in real-world inventory management.
Provides a foundation for enhanced inventory accuracy and reduced retail losses.