Abstract: In order to improve the protection of epidemic prevention during the epidemic and reduce the risk of spread caused by the movement of people,this paper uses face recognition and infrared temperature measurement technology to design intelligent epidemic prevention system, which first makes mask test and then face recognition, and adds infrared temperature measurement in identification. Upon completion of identity verification and temperature at the same time, the real-time monitoring results will be uploaded to the cloud, which improves epidemic prevention security effectively and reduce the disease spread risk. The experimental results show that the face recognition accuracy of intelligent epidemic prevention system designed in this paper can reach 98.57%, which reaches 98.11% after wearing masks, and the temperature detection is also more accurate. Compared with the simple application of face recognition in the field of identity verification, the added functions of infrared temperature measurement and mask detection meet the special needs of the epidemic period, which can be applied to a wide range of practical scenarios, and can effectively solve the problem of the complex epidemic prevention process and low real-time performance.

Key words: intelligent epidemic prevention, face recognition, infrared temperature measurement, the Internet of things 

摘要： 为提高疫情期间防疫保障，降低人员流动过程中带来的疫情传播风险；本文使用人脸识别和红外测温等技术进行智能防疫系统设计，先进行口罩检测，再进行人脸识别，并在识别部分增加红外测温功能，在完成身份核实及体温判断的同时，把监测结果实时反馈上云，有效地提高了防疫保障，降低疫情传播风险；实验结果表明，本文设计的人脸识别智能防疫系统人脸识别准确率达到98.57%，戴上口罩之后也可以达到98.11%，温度检测也比较准确；相比于人脸识别在身份核实领域的简单应用，增加的红外测温功能和口罩检测功能符合疫情时期特殊需求，能应用的实际场景广泛，能有效解决防疫过程过于复杂、实时性不高等问题。

关键词: 智能防疫, 人脸识别, 红外测温, 物联网