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Face Recognition System Integration​

Streamlining Attendance at IIITK with Facial Recognition

Introduction

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.

Challenge

Manual Attendance Tracking: Before implementing the facial recognition system, IIITK faced challenges with manual attendance tracking. Faculty members had to manually record attendance, leading to time-consuming and error-prone processes.

Proxy Attendance Issues: The manual system allowed class room for proxy attendance, where students could mark their peers present, leading to inaccurate attendance records and potential academic discrepancies.

Complex Integration: Integrating attendance data with the Learning Management System (LMS) was a significant challenge. IIITK needed a solution that seamlessly connected attendance records with their existing digital infrastructure.

Workload on Faculty: Faculty members had the burden of manually recording attendance, taking valuable time away from teaching and impacting their overall workload.

Solution

Brain Station 23, a technology solution provider, developed a machine learning-powered facial recognition system tailored to IIITK’s needs, such as-

Automated Attendance Tracking

The facial recognition system automates the attendance tracking process. Students can easily log in to their LMS using their mobile phones, activate the camera, and have their attendance recorded automatically. This streamlined process reduces the workload on faculty members.

Efficient Data Training and Accuracy

The system was trained on a diverse dataset of over 2,500 student’s faces, ensuring accuracy and reliability. After refining the training data, the system achieved an impressive accuracy rate of 95.6%. Real-time training further enhances the accuracy of the recognition process.

Seamless Integration with LMS

The system seamlessly integrates with the institute’s Learning Management System, providing a unified platform for attendance management and academic activities.

Reduced Proxy Attendance

By setting specific times for attendance submission, the system minimizes the possibility of proxy attendance. Students can only mark their attendance during designated periods, ensuring accuracy and accountability.

Positive User Experience

The system has received positive feedback from students who find it convenient. Faculty members no longer need to spend valuable class time on manual attendance tasks, allowing for a more focused and efficient learning environment.

Face recognition system for attendance tracking

Result

Efficient Attendance Tracking

Attendance tracking, once a time-consuming task, is now a swift process taking only 3 minutes for an entire class. This drastic reduction from 10-15 minutes per class has resulted in significant time savings for both faculty and students.

Reduced Workload and Enhanced Teaching

The automated system has alleviated the burden on staff, allowing them to focus on teaching. Faculty members now have an extra 7-12 minutes per class, leading to a more focused and engaging learning experience for students.

Improved Accuracy and Data Management

The facial recognition system ensures accurate attendance records, eliminating the possibility of errors and proxy attendance. This precision in data management has enhanced the overall reliability of academic records.

Improved Student Engagement

With the manual attendance burden lifted, faculty members can focus on teaching, leading to increased student engagement and a more conducive learning atmosphere.

Future Expansion and Innovation

The success of the system has inspired IIITK to explore further applications. The university plans to continue using the system and expand its implementation to other areas of the campus, indicating a positive trajectory toward more innovative solutions.

Enhanced Safety Measures

By accurately identifying individuals, the system contributes to campus safety. The face recognition system opens possibilities for restricting access to campus facilities, such as dormitories or research labs, to only authorized individuals thereby enhancing the overall safety of the student body.

In conclusion, the implementation of the facial recognition system at IIITK has not only addressed the immediate challenges related to attendance tracking but has also paved the way for a more technologically advanced and efficient educational environment. The seamless integration, accuracy, and positive user experiences highlight the success of this innovative solution in revolutionizing attendance management at IIITK.

Moreover, the broader significance of facial recognition can be seen in its growing market value, projected to reach $12.67B by 2028, and the fact that 70% of governments globally are using it widely, underscoring that it’s crucial not just for education industry but for modern infrastructures worldwide as well .

Services We Provide 

Brain Station 23 is focused on delivering tailored services to meet the unique needs and expectations of their clients. Here we provided AI & ML  Solutions to our client. 

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