Smart Attendance System using Deep Learning

This study has designed and developed a facial recognition-based attendance management system for educational. The manual attendance management system consumes more time and is difficult to maintain. This will be replaced by automatic attendance management system. The existing automated attendance management system is highly unreliable, resulting in inaccuracies and poor attendance maintenance records. Facial recognition technology will play a significant role in assisting these efforts. Facial recognition is one of the most effective biometric techniques. One of the natural traits that may be utilized to distinguish one person from another is face recognition. Hence, this study utilizes an approach based on Convolutional Neural Networks (CNN). Here, the face recognition dataset is trained to the proposed CNN model. Using the Open CV face recognition approach, an input image will be processed and a face will be detected and then a spreadsheet will also be utilized to record attendance. As soon as a person is recognized, the essential information gets stored in an excel spreadsheet, and finally the attendance will be recorded. A report containing the attendance data will then be sent to parents at the end of each school day. Moreover, the student's attendance information is sent to the parents via SMS. Additionally, this study recommended sending the parents a summary of the student's grades as well as attendance information. The primary objective of this study is to keep students and staff safe and fully present in class, as well as to eliminate the manual attendance marking method and save time.