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Conceptual Selective RFID Anti-Collision Technique Management
Author(s) -
Prapassara Pupunwiwat,
Peter Darcy,
Bela Stantić
Publication year - 2011
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2011.07.114
Subject(s) - computer science , collision , radio frequency identification , selection (genetic algorithm) , identification (biology) , wireless , quality (philosophy) , collision detection , tree (set theory) , data mining , real time computing , computer security , artificial intelligence , telecommunications , mathematical analysis , philosophy , botany , mathematics , epistemology , biology
Radio Frequency Identification (RFID) uses wireless radio frequency technology to automatically identify tagged objects. Despite the extensive development of RFID technology, tag collisions still remains a major drawback. The collision issue can be solved by using anti-collision techniques. While existing research has focused on improving anti-collision methods alone, it is also essential that a suitable type of anti-collision algorithm is selected for the specific circumstance. In this work, we evaluate anti-collision techniques and perform a comparative analysis in order to find the advantages and disadvantages of each approach. To identify the best anti-collision selection method in various scenarios, we have proposed two strategies for selective anti-collision technique management: a "Novel Decision Tree Strategy" and a "Six Thinking Hats Strategy". We have shown that the selection of the correct technique for specific scenarios improve the quality of the data collection which, in turn, will increase the integrity of the data after being transformed, aggregated, and used for event processing.Griffith Sciences, School of Information and Communication TechnologyFull Tex

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