Face recognition of remote monitoring under the Ipv6 protocol technology of Internet of Things architecture

Abstract

Abstract With the advent of the Internet of Things (IoT) era, the application of intelligent devices in the network is becoming more and more extensive, and the monitoring technology is gradually developing towards the direction of intelligence and digitization. As a hot topic in the field of computer vision, face recognition faces problems such as low level of intelligence and long processing time. Therefore, under the technical support of the IoTs, the research uses internet protocol cameras to collect face information, improves the principal component analysis (PCA), poses a PLV algorithm, and then applies it to the face recognition system for remote monitoring. The outcomes demonstrate that in the Olivetti Research Laboratory face database, the accuracy of PLV is relatively stable, and the highest and lowest are 98 and 94%, respectively. In Yale testing, the accuracy of this algorithm is 12% higher than that of PCA algorithm; In the database of Georgia Institute of Technology (GT), the PLV algorithm requires a time range of 0.2–0.3 seconds and has high operational efficiency. In the selected remote monitoring face database, the accuracy of the method is stable at more than 90%, with the highest being 98%, indicating that it can effectively improve the accuracy of face recognition and provide a reference technical means for further optimization of the remote monitoring system.