Real Time Face Recognition for Library Check in Check out System Using Deep Learning

Abstract

Face recognition is a way to identify or verify someone’s identity by using their face. Face recognition systems may be used to pick out humans in photographs, video, or in actual-time. The main objective of the project is to authenticate users including students, faculty and staff using their faces to maintain the data of those who are logged in and logged out from the library database. The student or faculty library login and logout information can be maintained in a smart way i.e. the count of the students and faculty as library users can be easily available and data of users such as entry and exit time will be stored. Face Recognition Phase can be done through Live Streaming. In previous days all the library login and logout information is stored in records manually which is a time taking process. There is a chance of data loss by maintaining books and it is difficult to maintain multiple records. Nowadays users are entering their identification details for check in and checkout to use the library. and RFID also uses in many library systems which comes under manually inserting the cards which is time taking procedure So the project mainly focuses on proposing a smart way to maintain faculty/student login and logout library information by using Convolution Neural Network (CNN) and also AWS is used in the project to securely store all the data on the cloud so that Database can access them from anywhere.