• Journal of the Korean Society for Railway
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• v.4 no.4
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• pp.155-161
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• 2001

In this paper, the method is suggested to prevent data collision or damage on RFID(Radio Frequency Identification) system, in case a reader reading multi-tag simultaneously, using binary-search algorithm and Time-domain anti-collision procedure at reader and tag, respectively. The RFID system is designed that Reader enable to communicate with Tag on 13.56MHz bandwidth which is ISM(Industrial Science Medical) bandwidth, antennas of Tag part are designed using MCRF335 Chip. When RF communication is achieved between reader and tag, in case that data is transmitted to reader pass through multiple tags simultaneously, a study on the anti-collision method for the situation that the data collision occurs is performed.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2006.10a
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• pp.176-183
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• 2006

A novel intelligent anti-collision decision-making supporting system is addressed in this paper. To obtain precise anti-collision information capability, an innovative neurofuzzy network is proposed and applied. A fuzzy set interpretation is incorporated into the network design to handle imprecise information. A neural network architecture is used to train the parameters of the Fuzzy Inference System (FIS). The learning process is based on a hybrid learning algorithm and off-line training data. The training data are obtained by trial manoeuvre. This neurofuzzy network can be considered to be a self-learning system with the ability to learn new information adaptively without forgetting old knowledge. This supporting system can decrease ship operators' burden to deal with bridge data and help them to make a precise anti-collision decision.

• ETRI Journal
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• v.30 no.5
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• pp.653-662
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• 2008

Arbitration of tag collision is a significant issue for fast tag identification in RFID systems. A good tag anti-collision algorithm can reduce collisions and increase the efficiency of tag identification. EPCglobal Generation-2 (Gen2) for passive RFID systems uses probabilistic slotted ALOHA with a Q algorithm, which is a kind of dynamic framed slotted ALOHA (DFSA), as the tag anti-collision algorithm. In this paper, we analyze the performance of the Q algorithm used in Gen2, and analyze the methods for estimating the number of slots and tags for DFSA. To increase the efficiency of tag identification, we propose new tag anti-collision algorithms, namely, Chebyshev's inequality, fixed adjustable framed Q, adaptive adjustable framed Q, and hybrid Q. The simulation results show that all the proposed algorithms outperform the conventional Q algorithm used in Gen2. Of all the proposed algorithms, AAFQ provides the best performance in terms of identification time and collision ratio and maximizes throughput and system efficiency. However, there is a tradeoff of complexity and performance between the CHI and AAFQ algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.3A
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• pp.184-194
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• 2005

One of the most important factors that decide the overall performance of RFID system is anti-collision algorithm. By enhancing the anti-collision algorithm, we can increase the number of RFID tags that can be processed in unit time. Two anti-collision algorithms are most widely prevailed: one is ALOHA-based protocol and the other is a binary tree walking method, but these are still under research. In this paper, we suggest an anti-collision algorithm named AAC(Address Allocating and Calling) using pre-distributed random address, which is much faster and more efficient than existing ones. Finally, we evaluate our scheme using mathematical analysis and computer simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.4A
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• pp.358-364
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• 2007

RFID, Radio Frequency Identification, technology is a contactless automatic identification technology using radio frequency. For this RFID technology to be widely spread, the problem of multiple tag identification, which a reader identifies a multiple number of tags in a very short time, has to be solved. Up to the present, many anti-collision algorithms have been developed in order to solve this problem, and those can be largely divided into ALOHA based algorithm and tree based algorithm. In this paper, two new anti-collision algorithms combining the characteristics of these two categories are presented. And the performances of the two algorithms are compared and evaluated in comparison with those of typical anti-collision algorithms: 18000-6 Type A, Type B, Type C, and query tree algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.10B
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• pp.885-893
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• 2008

In RFID system, reader collision happened when multiple readers try to read the tags at the same time. Because reader collision reduces tag recognition performance, it is required for RFID system to have reader anti-collision algorithm. In this paper, we propose reader anti-collision algorithm based on hierarchical structure, where a master reader controls the slave readers to avoid the reader collisions. It is verified through simulations that the proposed algorithm enhances the performance in terms of leader collision probability and tag reading time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1460-1478
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• 2020

This paper proposes a novel anti-collision protocol for large-scale RFID tags identification, named Bi-response Collision Tree Protocol (BCT). In BCT, two group of tags answer the reader's same query in two response-cycles respectively and independently according to the bi-response pattern. BCT improves the RFID tag identification performance significantly by decreasing the query cycles and the bits transmitted by the reader and tags during the identification. Computation and simulation results indicate that BCT improves the RFID tag identification performance effectively, e.g. the tag identification speed is improved more than 13.0%, 16.9%, and 22.9% compared to that of Collision Tree Protocol (CT), M-ary Collision Tree Protocol (MCT), and Dual Prefix Probe Scheme (DPPS) respectively when tags IDs are distributed uniformly.

• Journal of Information Technology Services
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• v.12 no.3
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• pp.331-343
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• 2013

In RFID systems, the anti-collision algorithm is being improved to recognize Tag's ID within recognition area of the reader quickly and efficiently. This paper focuses on Tag collision. Many studies have been carried out to resolve Tag collision. This paper proposes a new N-ary Query Tree Algorithm to resolve more than Tag collision simultaneously, according to the value of m(2 ~ 6). This algorithm can identify more tags than existing methods by treating a maximum 6 bit collision, regardless of the continuation/non-continuation Tag's ID patterns. So, it extracts maximumly different $2^6$ bit patterns per single prefix in recognition process. The performance of N-ary Query Tree Algorithm is evaluated by theoretical analysis and simulation program.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.8A
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• pp.805-814
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• 2008

Both EPCglobal Generation-2 (Gen2) for passive RFID systems and Intelleflex for semi-passive RFID systems use probabilistic slotted ALOHA with Q algorithm, which is a kind of dynamic framed slotted ALOHA (DFSA), as the tag anti-collision algorithm. A better tag anti-collision algorithm can reduce collisions so as to increase the efficiency of tag identification. In this paper, we introduce and analyze the estimation methods of the number of slots and tags for DFSA. To increase the efficiency of tag identification, we propose two new tag anti-collision algorithms, which are Chebyshev's inequality (CHI) algorithm and hybrid Q algorithm, and compare them with the conventional Q algorithm and adaptive adjustable framed Q (AAFQ) algorithm, which is mentioned in Part I. The simulation results show that AAFQ performs the best in Gen2 scenario. However, in Intelleflex scenario the proposed hybrid Q algorithm is the best. That is, hybrid Q provides the minimum identification time, shows the more consistent collision ratio, and maximizes throughput and system efficiency in Intelleflex scenario.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.9
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• pp.1564-1568
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• 2008

The anti-collision system is one of units for effectual operation and safety in crane operation. Most of the system have used ultrasonic to measure position and to prevent collision of crane. But, the anti-collision system using ultrasonic is fallen the reliability of performance by the change of temperature and humidity. Hence, this study proposes neural network applied to anti-collision system to improve accuracy and stability of the measured distance data, and we evaluate performance of the system. In results of experiments, the proposed method was seen that stability and accuracy of data are improved than that of the temperature compensation method.