基于射频技术与智能动作识别的人员身份认证方法研究

Research on personnel identity authentication method based on radio frequency technology and intelligent action recognition

针对大部分身份认证方法存在认证方式单一、认证准确性低等问题,文中在医用场景下开展了基于射频技术与智能动作识别的人员身份认证方法研究。在详细论述无线射频识别技术(RFID)及其系统构成后,基于深度学习网络中的t-SNE降维处理、支持向量机动作分类等技术,设计实现了智能动作识别方法。将通过RFID和智能动作识别方法获得的身份信息输入长短时记忆网络进行处理分析,从而得到最终的身份认证结果。基于Python仿真平台对所提方法进行实验分析,结果表明,文中所提方法的认证准确率与时间开销分别为94.51%和31 ms,明显优于其他对比方法,具有良好的应用前景。

Aiming at the problems of single authentication method and low accuracy in most identity authentication methods,this paper carried out the research of personnel identity authentication method based on radio frequency technology and intelligent action recognition in medical scene. After discussing the Radio Frequency Identification(RFID) technology and its system structure in detail,the intelligent action recognition method is designed and implemented based on t-SNE dimension reduction processing and support vector machine classification technology in deep learning network. The identity information obtained by RFID and intelligent action recognition method is input into the long-term and short-term memory network for processing and analysis,and the final identity authentication result is obtained. The experimental results based on Python simulation platform show that the authentication accuracy and time cost of the proposed method are 94.51% and 31 ms respectively,which are significantly better than other comparison methods and have good application prospects.