Contribution to attendance and fraud management in engineering schools and digital universities with Deep Learning

Facial recognition is applied in many sectors, including education. In fact, in engineering schools, where one of the major challenges is to train students in different sectors of activity, the presence of students is fundamental during these courses, unlike in faculties where attendance is not mandatory during lectures. In the face of massification in digital universities, the management of attendance and fraud during evaluations becomes fundamental to the credibility of the diplomas issued. This paper presents an artificial intelligence-based facial recognition system for attendance and fraud management in engineering schools and digital universities. Attendance and exam fraud management play a very important role in the training of learners. The use of this system saves a lot of time by eliminating the attendance management step by automating it while detecting fraud during exams. The solution consists of a student, course and schedule management application coupled with a facial recognition system. It detects the presence of learners during scheduled lessons and assessments through facial recognition.