PISS-IoT:物联网方式的人员识别和定位系统

Harish Ram Nambiappan, S. Datta
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引用次数: 0

摘要

失踪人口已成为世界上许多国家最严重的问题之一。事实上,这不仅使那些失去亲人的人感到担忧,而且也使执法官员感到担忧,因为他们要搜查并找到亲人。因此,考虑到这种问题陈述,我们创建了一个使用物联网概念的人员识别和定位系统。我们的系统使用安卓手机摄像头和一个服务器系统编码的LBPH面部识别和电子邮件发送功能。所有这些组件都通过亚马逊AWS云以物联网的方式相互连接。与之前的工作相比,这是一种独特、新颖、可扩展和更好的方法,因为我们的系统不是专注于单个设备的人脸检测和识别,而是将人脸检测摄像头与运行在其他地方的人脸识别和验证系统连接起来。此外,我们的系统还包括通过云与身份识别系统互连的自动邮件发送组件,这在以前的工作中都没有实现过。在大学校园的不同地点与真实的受试者进行了实时实验,该系统运行得非常好,从检测到人脸到通知用户发现位置的平均时间在30秒到1分40秒之间,平均准确率在92%到96%之间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PISS-IoT: Person Identification and Spotting System in an Internet-of-Things Way
Missing persons has become one of the most serious issues in many countries around the world. It has been a fact to worry not only for those persons who lost their relatives but also for the law and order officials to search them and find them. So with this kind of problem statement in mind we have created a person identification and spotting system using the Internet-of-Things concept. Our system uses android mobile phone cameras and a server system coded with LBPH Facial recognition along with email sending functions. All these components are interconnected through Amazon AWS cloud in an Internet-of-Things fashion. This is a unique, novel, scalable and better approach, when compared to the previous works because instead of focusing on face detection and recognition in just a single device, our system involves interconnection of face detecting cameras with the face recognition and verification system which is running elsewhere. Also, our system includes the automatic email sending component interconnected with the identification system through cloud which has not been performed in any of the previous works. Experiments were conducted in real-time with real subjects at various locations around the university campus and the system worked very well where the average timings measured from the detection of face till notifying the user with the spotted location was within the range of 30 seconds to 1 minute and 40 seconds with an average value of accuracy ranging from 92 to 96 percent.
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