A Review of - Smart Attendance Monitoring System Using Raspberry Pi

Our project illustrates the importance of automation in the present world using the concept of face recognition. As we all know, a person's face plays a significant role in establishing their identity. This project consists of OpenCV algorithm modules running in Python. This effort also gives people hope for greater improvisation and fresh thinking in light of impending advancements in hardware and technology. The model has a 99.38% accuracy rate and offers a straightforward command line utility for face recognition. This tool is superior to generic algorithms because it just requires one image to work with and does not require grayscale conversion. Thousands of samples are required for the Haar cascade, LBPH, and Eigenface algorithms to determine the distance between points and pixels in an image. The Raspberry Pi's built-in email functionality is used to utilize IOT. We're helped in this via SMT Protocol. There may be plans for the project to boost model accuracy and speed in the future.

Autorentext

Il sig. K. Rama Krishna lavora come professore assistentepresso il Dipartimento di Elettronica e ComunicazioneKKR AND KSR INSTITUTE OF TECHNOLOGY AND SCIENCES, con una specializzazione in Segnali e sistemi, Elettronica digitale e sistemi di comunicazione e Antenne intelligenti. Ha una buona esperienza di ricerca e ha pubblicato diversi articoli di ricerca.