A knowledge-based Query Tree with Shortcutting and Couple-Resolution for RFID tag identification

Hailemariam, Zelalem Legese; Lai, Yuan‐Cheng; Jayadi, Riyanto; Chen, Yen-Hung; Huang, Sheng-Chi

doi:10.1016/j.comcom.2020.06.025

Cited by 8 publications

(8 citation statements)

References 24 publications

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“…Our designed simulator was validated by Equations (3)-(6) in our previous works [21][22][23][24], which demonstrated the mathematical analysis results match the simulation results of our designed RFID simulator very well. The simulator adopted in this study is extended by simulator developed by our previous works [21][22][23][24]. To ensure the experiments were simulated in a verisimilar environment, we derived the corresponding numerical analysis model in Ref.…”

Section: Resultsmentioning

confidence: 59%

“…Our designed simulator was validated by Equations (3)-(6) in our previous works [21][22][23][24], which demonstrated the mathematical analysis results match the simulation results of our designed RFID simulator very well. As shown in Figure 13, the rate of the conveyor belt was one meter per second (1 m/s), and measurements were in units of 0.5 m. The performance of SAC and MABT in terms of MAD (mean absolute deviation), MSE (mean square error), and MAPE (mean absolute percent error) are also demonstrated in Figure 13.…”

Section: Resultsmentioning

confidence: 59%

“…Since MABT and SAC use the same estimation formula to determine optimal group size, the same value can be used. The simulator adopted in this study is extended by simulator developed by our previous works [21][22][23][24]. To ensure the experiments were simulated in a verisimilar environment, we derived the corresponding numerical analysis model in Ref.…”

Section: Resultsmentioning

confidence: 99%

“…To ensure the experiments were simulated in a verisimilar environment, we derived the corresponding numerical analysis model in Ref. [21][22][23][24] by the following equations.…”

Section: Resultsmentioning

confidence: 99%

“…The simulator adopted in this study is extended by simulator developed by our previous works [ 21 , 22 , 23 , 24 ]. To ensure the experiments were simulated in a verisimilar environment, we derived the corresponding numerical analysis model in Ref.…”

Section: Resultsmentioning

confidence: 99%

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A Mobility Aware Binary Tree Algorithm to Resolve RFID Jam and Bottleneck Problems in a Next Generation Specimen Management System

Chen

Huang

2020

Micromachines

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Hospitals are continuously working to reduce delayed analysis and specimen errors during transfers from testing stations to clinical laboratories. Radio-frequency identification (RFID) tags, which provide automated specimen labeling and tracking, have been proposed as a solution to specimen management that reduces human resource costs and analytic delays. Conventional RFID solutions, however, confront the problem of traffic jams and bottlenecks on the conveyor belts that connect testing stations with clinical laboratories. This mainly results from methods which assume that the arrival rate of specimens to laboratory RFID readers is fixed/stable, which is unsuitable and impractical in the real world. Previous RFID algorithms have attempted to minimize the time required for tag identification without taking the dynamic arrival rates of specimens into account. Therefore, we propose a novel RFID anti-collision algorithm called the Mobility Aware Binary Tree Algorithm (MABT), which can be used to improve the identification of dynamic tags within the reader’s coverage area and limited dwell time.

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Section: Resultsmentioning

confidence: 59%

“…Our designed simulator was validated by Equations (3)-(6) in our previous works [21][22][23][24], which demonstrated the mathematical analysis results match the simulation results of our designed RFID simulator very well. As shown in Figure 13, the rate of the conveyor belt was one meter per second (1 m/s), and measurements were in units of 0.5 m. The performance of SAC and MABT in terms of MAD (mean absolute deviation), MSE (mean square error), and MAPE (mean absolute percent error) are also demonstrated in Figure 13.…”

Section: Resultsmentioning

confidence: 59%

Section: Resultsmentioning

confidence: 99%

“…To ensure the experiments were simulated in a verisimilar environment, we derived the corresponding numerical analysis model in Ref. [21][22][23][24] by the following equations.…”

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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A Mobility Aware Binary Tree Algorithm to Resolve RFID Jam and Bottleneck Problems in a Next Generation Specimen Management System

Chen

Huang

2020

Micromachines

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A distinguished-bit tracking knowledge-based query tree for RFID tag identification

Lin,

Lai,

Hailemariam

2024

Computer Communications

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Wireless Power Supply Sensing Tags Based on Anti-Collision Algorithm for Sensing Systems

2024

IEEE Access

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In wireless sensor networks, sensing tags are battery powered, which also limits the battery life. Therefore, it is particularly important to study self powered sensing tags. At present, passive wireless identification systems can achieve self powered communication through tags.However, wireless power supply sensing systems have problems such as low efficiency and short communication distance. To reduce the power consumption of sensing tags and improve the efficiency of sensing systems, a passive wireless low-power hydrogen concentration sensing system is designed. To further reduce the power consumption of sensing tags, a passive wireless magnetic field intensity sensing system is developed.In addition, to solve the low efficiency of multiple sensing labels in wireless power supply sensing systems, an efficient anticollision algorithm based on dynamic binary query trees is designed. According to the research results, in the cold start indoor environment, the energy collection rate of the sensing tag designed in the research was 0.081mJ/s, and the energy collection efficiency was 25.7%.In single/dual sensor mode, the maximum values of sensing error were 2.1% and 5.2%, respectively. The maximum recognition time of the anticollision algorithm based on dynamic multi base query tree was 2.78s, and the minimum value was 1.31s.The research results can provide methodological and technical support for the improvement of wireless power supply sensing systems, expanding the application range of wireless power supply sensing systems.

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A knowledge-based Query Tree with Shortcutting and Couple-Resolution for RFID tag identification

Cited by 8 publications

References 24 publications

A Mobility Aware Binary Tree Algorithm to Resolve RFID Jam and Bottleneck Problems in a Next Generation Specimen Management System

A Mobility Aware Binary Tree Algorithm to Resolve RFID Jam and Bottleneck Problems in a Next Generation Specimen Management System

A distinguished-bit tracking knowledge-based query tree for RFID tag identification

Wireless Power Supply Sensing Tags Based on Anti-Collision Algorithm for Sensing Systems

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