Research on RFID Location Application of Particle Swarm Neural Network Algorithm
ZHOU Leilei1a, LIU Chengyou1a, MA Jun1b, QIN Hang1a, JIANG Hongbing1a,2
1.a.Department of Medical Equipment; b.Department of Faculty, Nanjing First Hospital, Nanjing Medical University, Nanjing Jiangsu
210006, China; 2.Centralized Drug Procurement Hosting Center, Nanjing Health Information Center, Nanjing Jiangsu 210003, China
Abstract:Objective To explore the application of radio frequency tag technology (RFID) in the management of medical equipment.
Methods A particle swarm optimization-back propagation (PSO-BP) localization algorithm based on RFID was proposed. The
experimental platform was firstly be built, and passive tags was sticked to the surface of the card to simulate the actual medical
equipment. Each label was assigned a unique device code. Received signal strength indication (RSSI) corresponding to the radio
frequency label coordinates in the experimental area was measured from three different angles, and the measurement data was then
preprocessed. Based on the experimental data, the PSO-BP model was trained under the established training error, and the mapping
between the RFID reader and the tag was obtained. The data of the unknown group were tested by the PSO-BP model after training.
Results Under the PSO-BP localization algorithm, the measured error between the measured and the original values reached
millimeter-level. Conclusion This algorithm associates the RSSI value with the position information, and avoids the estimation of
parameter value when the RSSI value is converted to distance, which can improve the accuracy of indoor positioning.
周蕾蕾1a,刘成友1a,马俊1b,秦航1a,蒋红兵1a,2. 粒子群神经网络算法的RFID定位应用研究[J]. 中国医疗设备, 2018, 33(2): 33-36.
ZHOU Leilei1a, LIU Chengyou1a, MA Jun1b, QIN Hang1a, JIANG Hongbing1a,2. Research on RFID Location Application of Particle Swarm Neural Network Algorithm. China Medical Devices, 2018, 33(2): 33-36.