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Retailers grapple with inventory losses primarily due to missing items, prompting the need for efficient missing tag identification methods in large-scale RFID systems. Among them, few works considered the effect of unexpected unknown tags on the missing tag identification process. With the presence of unknown tags, some missing tags may be falsely identified as present. Thus, the system's reliability is hardly guaranteed. To resolve these challenges, we propose an efficient early-breaking-estimation and tree-splitting-based missing tag identification (ETMTI) protocol for large-scale RFID systems. ETMTI employs innovative early-breaking-estimation and deactivation methods to swiftly handle unknown tags. Subsequently, a tree-splitting-based missing tag identification method is proposed, employing a B-ary splitting tree, to rapidly identify missing tags. Additionally, a bit-tracking response strategy is implemented to reduce processing time. Theoretical analysis is conducted to determine optimal parameters for ETMTI. Simulation results illustrate that our proposed ETMTI protocol significantly outperforms benchmark methods, offering a shorter processing time and a lower false negative rate. [ABSTRACT FROM AUTHOR]

As one of the key techniques used in the perception layer of the Industrial Internet of Things (IIoT), radio frequency identification (RFID) has been widely applied for object tracing, smart warehouse management, product line monitoring, etc. In most applications, conveyor belts are prevalently implemented to accelerate the sorting efficiency for goods management. However, in such a system, tags quickly go through the reader's reading range resulting in constant changing of the tag set and limited participating time of moving tags. As a result, it poses more challenges to the tag identification problem in mobile systems than in traditional static applications. In this work, a novel admission-control-based dynamic query tree (ACDQT) protocol is proposed for fast-moving tag identification. In ACDQT, two main strategies are developed, i.e., multi-round admission control (MRAC) and dynamic query tree recognition (DQTR). In MRAC, the reading process of multiple rounds is analyzed, and the number of admitted tags in each round is optimized. Thus, the tag lost ratio is guaranteed, and the identification process can be effectively accelerated. In DQTR, colliding tags are grouped into multiple subsets with the help of consecutive colliding bits in tag responses. By constructing a dynamic query tree, the number of collision slots is greatly reduced, and the identification efficiency in a single round is improved significantly. With MRAC and DQTR, ACDQT can support higher tag flow rate in mobile systems than existing works. Both theoretical analyses and simulation results are presented to demonstrate the effectiveness of ACDQT. [ABSTRACT FROM AUTHOR]

In passive radio frequency identification (RFID) systems, the capture effect may occur that the reader is possible to successfully decode the strongest signal when multiple tags reply simultaneously. In this situation, the weaker signals will be covered resulting in a tag hidden problem which greatly affects the system performance. To solve the problem, a bit-detecting M-ary tree (BMT) protocol was proposed. First, a bit-detecting tag number estimation method was proposed to estimate the number of tags and group them with a few slots. Next, an M-ary tree protocol was developed to eliminate all the idle slots and identify tags quickly. At the same time, a hash muting strategy was given to mute the identified tags and label the hidden ones with small communication cost. Both theoretic analysis and simulation results demonstrate that BMT can effectively reduce the identification delay by at least 15%. [ABSTRACT FROM AUTHOR]