Problem

Our college's IoT lab was facing issues with their attendance system. The previous system was manual and prone to errors, leading to inaccurate attendance records. This caused a lot of inconvenience for both the students and faculty members.

We were tasked with developing an automated attendance system that would eliminate these issues and provide accurate attendance records in real-time.

Solution

Our team of three decided to develop an AI face recognition system that would use transfer learning by downloading pre-trained models. We used Python programming language and OpenCV library for this project. We trained our model on a dataset of student images provided by the IoT lab.

The system works by capturing an image of the student's face using a camera at the entrance of the lab. The image is then processed by our AI model, which recognizes the student's face and marks their attendance in real-time. We also integrated API's and database management to store the data in the club's database.

Impact

Eliminated errors in attendance records
Provided accurate attendance records in real-time
Reduced time spent on manual attendance taking
Increase efficiency of faculty members
X% increase in overall lab productivity due to automated attendance system
X% reduction in absenteeism due to accurate tracking of attendance records

Team

Rahul Sharma - Project Manager/Lead Developer
- Oversaw project development from start to finish, managed team tasks, ensured timely delivery of project milestones
Akash Singh - AI Developer
- Developed the AI model using Python and OpenCV library, trained the model on a dataset of student images
Riya Gupta - Database Manager/API Developer
- Managed the database for the club, integrated API's to store attendance data in real-time

Automated AI Face Recognition Attendance System