以医院手术工勤人员的全流程智慧追溯为建设场景,以改善射频识别(Radio Frequency Identification,RFID)物联网手术工勤人员定位精度低、鲁棒性差问题为研究目标,提出一种基于卡尔曼滤波和图基平滑的室内定位优化方法,增强定位准确性.该研究首先以图的数据结构对场景进行建模,接着基于卡尔曼滤波(Kalman Filtering)和图基平滑(Tukey Smoothing)算法建立RFID室内定位优化方法,最后通过定位优化模块改善手术工勤人员定位追溯的成效.实证分析结果表明:该方法能有效改善定位精度,方法应用的3个月内手术工勤人员追溯准确率为99.75%.
Optimization Method of RFID Surgical Service Workers Positioning and Traceability Based on Kalman Filter and Tukey Smoothing
Taking the intelligent traceability of the whole process of hospital surgical workers as the construction scenario,and improving the low positioning accuracy and poor robustness of Radio Frequency Identification(RFID)Internet of Things surgical workers as the research goal,An indoor location optimization method based on Kalman Filter and Tookey Smoothing is proposed to enhance the location accuracy.In this study,the scene was first modeled using the graph data structure,and then the RFID indoor positioning optimization method was established based on Kalman Filter and Tukey Smoothing algorithm.Finally,the positioning optimization module was used to improve the positioning and tracing effectiveness of surgical workers.The results of empirical analysis show that the method can effectively improve the positioning accuracy,and the accuracy of surgical service workers trace within 3 months of application of the method is 99.75%.
Surgical service workersAlgorithmIndoor positioningKalman FilterTukey SmoothingRFID
NETL
NSTL
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