The Indian Institute of Information Technology, Kottayam (IIITK) is an autonomous engineering institute located in Valavoor, Palai, Kottayam District, Kerala, India.
The institution is dedicated to creating a specialized group of information technology professionals by providing high-quality education and training programs. The aim of the institute is to reach international standards in its research, teaching, and consulting efforts and establish a worldwide network.
The Indian Institute of Information Technology, Kottayam (IIITK) they were looking to implement a facial recognition system for attendance tracking in their classrooms to streamline and enhance accuracy. That system’s goal was to simplify attendance- tracking more efficiently and accurately and integrate it with their Learning Management System (LMS) and reduce the workload on faculties who had to manually take attendance.
Brain Station 23 has developed a machine learning-powered face recognition system to automate the attendance tracking. The system was initially trained on a large dataset of over 2,500 student’s faces and after refining the training data for a month, the final product achieved a 95.6% accuracy rate in identifying individual students. The system also allows for real-time training to improve accuracy.
To utilize the system, students simply need to login to their LMS via mobile phone and select a specific class in that LMS. The system provides the option to activate the camera, which captures an image of the student. The image is then processed through the face recognition model, and if the student is successfully identified, their attendance for that class is recorded automatically. The system streamlines the attendance tracking process and eliminates the need for manual efforts.
The face recognition system has been highly effective with minimal false identification and high accuracy. The system has received positive feedback from students who appreciate its convenience, while faculty no longer need to spend time manually taking attendance.
Furthermore, with the help of its attendance tracking capabilities, the system has also improved overall class attendance by allowing faculty to set specific times for attendance system where students just need to submit their attendance on that specific time. This reduces the occurrence of proxy attendance. The system’s capacity to accurately identify individual students also open up the possibility for future usage in restricting access to campus facilities, such as dormitories or research labs, to only authorized individuals.
The introduction of the face recognition system had a significant impact on the operations at the Indian Institute of Information Technology, Kottayam (IIITK). It streamlined attendance tracking, reduced workload on staff, and automated the calculation of attendance marks. The time required for taking attendance was reduced from 10-15 minutes per class to just 3 minutes for the entire class, regardless of student count, freeing up 7-12 minutes per class for a more focused on teaching & learning experience.
The success of the system has prompted the university to continue its usage in the future and consider its implementation in other areas of the campus as well. The face recognition system positively impacted the efficiency and effectiveness of attendance tracking at IIITK.
Overall, implementing a facial recognition system for attendance tracking in classrooms can bring numerous benefits to the business of education. These benefits not only limited to increased accuracy and timesaving through enhanced data management for the faculties but also improved student engagement, increased student safety, and convenience.