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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.

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