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An Efficient Estimation Method Coping with the Capture Effect for RFID Tags Identification and Application in Remote Learning

Yang, Lvqing, Zhang, Gouging, Lin, Fan and Zheng, Huiru (2016) An Efficient Estimation Method Coping with the Capture Effect for RFID Tags Identification and Application in Remote Learning. Journal of Intelligent & Fuzzy Systems Special Issue: Multimedia inTechnology Enhanced Learning, 31 (5). pp. 2707-2712. [Journal article]

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DOI: 10.3233/JIFS-169110

Abstract

In telecommunications, the capture effect is a phenomenon associated with frequency modulation reception in which two strong signals at, or near, the same frequency or channel will be demodulated. In wireless networks, a frame collision does not necessarily result in all the simultaneously transmitted frames being lost. Depending on the relative signal power and the arrival time of the involved frames, one frame can survive the collision and be successfully received by the receiver. Efficient object identification with passive RFID tags. In former works, many researches focus on the RFID anti-collision protocol only, however, less did pay special attention to the capture effect mainly to keep the design simple and cost low. Nonetheless, the capture effect occurs frequently in real deployments. In this paper, we have taken the capture effect into consideration and combined this thought to an efficient RFID anti-collision protocol, then proposed an efficient method to estimate the optimal frame length to adjust the quantity of RFID tags. After setting an optimal frame length by using the proposed method, furthermore, we obtained higher identification efficiency. RFID technology can be used for real-time recording and tracking of the learning process, which comprises real-time records of learners and their partners learning process such as experience, debate, cooperation, competition, problem solving, and other learning experiences.

Item Type:Journal article
Keywords:Capture effect; Vogt algorithm; RFID
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Research Institutes and Groups:Computer Science Research Institute > Smart Environments
Computer Science Research Institute
ID Code:35130
Deposited By: Dr Huiru Zheng
Deposited On:19 Jul 2016 13:08
Last Modified:22 Feb 2018 17:00

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