New anti-collision protocol for RFID-based student attendance system

Conference Title: 2018 2nd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) Conference Start Date: 2018, Oct. 19 Conference End Date: 2018, Oct. 21 Conference Location: Ankara, Turkey The importance of Radio Frequency Identification (RFID) systems comes from...

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Bibliographic Details
Published inThe Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings p. 1
Main Authors Sharabaty, Hassan, Zencir, Ertan, Hameed, Ghassan Ali
Format Conference Proceeding
LanguageEnglish
Published Piscataway The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 01.01.2018
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Summary:Conference Title: 2018 2nd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) Conference Start Date: 2018, Oct. 19 Conference End Date: 2018, Oct. 21 Conference Location: Ankara, Turkey The importance of Radio Frequency Identification (RFID) systems comes from its ability to communicate remotely with others devices in spite of barriers, obstacles, walls or even the water. RFID also offers a highspeed processing for all operations performed by these systems. The main parts of any RFID system are tags and reader. However, the tags collision problem affects the performance and the accuracy of the identification process. In this paper, we propose a new anti-collision protocol to reduce the tags collisions that take place in RFID based student attendance system. Firstly, development of the two conventional anti-collusion methods is proposed: Dynamic Framed Slotted ALOHA (DFSA), and Basic Framed Slotted ALOHA (BFSA), then, we combine both methods in a novel anti-collision protocol to accelerate the identification process. Comparing to other conventional anti-collusion techniques in the literature, the simulation results show that our proposed protocol decreased the time and slots consumption of the authentication process by 26%. The throughput of the identification process is also increased by approximately 10%, while the number of collided tags are reduced by 49%.