AI‐Based Surveillance Systems for Effective Attendance Management

Summary

The traditional system of attendance requires maintaining an attendance register and manually noting the attendance of every student. This system is prone to errors and marking of proxy attendance. The solution lies in use of deep learning technologies to automate the process. These techniques use face recognition and identification to instantly identify people. They are used extensively in real‐time security surveillance systems. These techniques are also being applied in Automatic Attendance Management (AAM) at various institutions.

This chapter is divided into nine sections. The first section discusses the importance of managing student attendance and the problems associated with traditional attendance management systems. This is followed by a discussion of Artificial Intelligence (AI) and Smart Surveillance, and Artificial Intelligence (AI) and Attendance Management. The next section is an overview of various image processing technologies in Automatic Attendance Management, and after that the discussion delves into deep Learning and Various Neural Network Techniques for Attendance Management. Further sections discuss the role of AI Technologies in Attendance Management, the challenges and opportunities for the deep learning technique‐based face recognition techniques. Finally, there is a discussion and conclusion.