Dual-spectrum intelligent temperature detection and health big data management system
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摘要:
公共安全视频监控在新型冠状病毒肺炎防治攻坚战中发挥了重要作用。针对中国人口密度高、人流量大、新型冠状病毒肺炎易传播的特点,建立了融合可见光和红外光双光谱成像监控的智能体温检测与健康大数据管理系统,实现了无接触快速体温检测与佩戴口罩情况下的人脸识别,快速完成人员信息登记。系统已在多地完成部署,通过了有效性和可靠性验证,测量速度快,响应时间在30 ms以内;测量精度高,测量温度误差在±0.3℃以内;测量范围广,可监控距离0.1~10 m;人脸抓拍率99%以上,识别率95%以上;健康大数据管理系统能实时监控和追踪回溯人员流动,在多维度上对人员信息和疫情发展大数据进行统计分析,并对疫情发展动态进行建模和预测,根据分析结果完善疫情防控策略,开展精准高效的疫情防控。
Abstract:Public safety video surveillance has played an important role in the battle against Corona virus disease 2019. Aimed at the characteristics of high population density, large flow of people, and the easy spread of Corona virus disease 2019 in China, an intelligent temperature detection and health big data management system combining visible and infrared dual-spectral imaging monitoring is established to achieve contactless rapid temperature detection and face recognition while wearing a mask, and to quickly complete the registration of personal information. The system has been deployed in multiple places, and has passed the verification of effectiveness and reliability. The measurement speed is fast and the response time is within 30 ms. The measurement accuracy is high and the measurement temperature error is within ±0.3℃. The measurement range is wide and the monitoring distance is 0.1-10 m. The face capture rate is over 99%, and the recognition rate is over 95%. The health big data management system can monitor and track back-to-back personnel movements in real time, perform statistical analysis on personnel information and epidemic development big data in multiple dimensions, conduct epidemic development trends modeling and prediction, improve epidemic prevention and control strategies based on the analysis results, and carry out accurate and efficient epidemic prevention and control.
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Key words:
- deep learning /
- video surveillance /
- dual-spectrum /
- temperature detection /
- epidemic situation
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表 1 不同场景下的体温检测情况
Table 1. Temperature detection in different scenes
人员 系统响应时间/ms 体温测量误差/℃ 戴口罩人脸识别情况 场景1 场景2 场景3 A 30 -0.1 0 -0.3 成功 B 20 0.1 -0.2 -0.1 成功 C 20 0.2 -0.1 -0.2 成功 D 25 0.2 -0.1 -0.1 成功 E 30 0.2 0.3 -0.2 成功 F 25 -0.2 0.2 -0.3 成功 G 20 -0.3 0 -0.2 成功 -
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