Taking attendance is one of the most crucial duties that must be performed every day in schools, institutions, and organizations. Most of the time, it is done manually using methods like verbal identification or roll call.

 

Our project’s primary objective is to develop an automatic attendance system called Smart Attend for an educational environment. Our System uses facial recognition technology, to replace the current manual attendance procedures which are inefficient, often inaccurate, and time-consuming, thereby reducing working productivity and learning time and having an impact on evaluation and documentation accuracy. Additionally, such manual methods lack real-time tracking, making it difficult to efficiently manage and confirm attendance, particularly in large groups.

 

Our Smart Attend System presents an innovative solution to managing attendance through the integration of hardware and software components. The system detects and recognizes faces using a webcam before matching them to their respective IDs. It records the attendance in the database and reflects the attendance records on a web application. The system uses a facial detection model that’s developed using deep convolutional neural network to register and identify faces. The system also uses a face recognition model that identifies a face between the ones already registered. The Smart Attend online web application offers a full user interface for organizing and viewing attendance data by providing separate login channels for instructors and students. Instructors can view complete attendance data for all their courses and can also record attendance for students. Students on the other hand can track their attendance in each of their registered courses.