Automating Student attendance System Using Face Recogniton


Our client is a Leading Coaching Institute of Central India preparing a huge number of students for various entrance exams. The firm is headquartered in India. The client sought our expertise in automating attendance process in the classroom using advance technologies like face detection and recognition. The development team came up with an innovative solution to meet the need of the client. The solution eased the process of marking attendance with good accuracy.

Technologies and tools

- Python
- Flask
- Machine Learning
- Face Detection & Recognition

Our Roles

- Front end and Back-end Development
- Mobile Application Development
- Project Management

Team Size

4 members


Administrators of School and Tuition Classes

The Challenge: To automate Student attendance system using Face Recognition

Identification of individuals in a class for attendance is one such application of face recognition. Maintenance and monitoring of attendance records play a vital role in the analysis of the performance of any organization. The purpose of developing an attendance management system is to computerize the traditional way of taking attendance. Automated Attendance Management System performs the daily activities of attendance marking and analysis with reduced human intervention. The prevalent techniques and methodologies for detecting and recognizing face fail to overcome issues such as scaling, pose, illumination, variations, rotation, and occlusions.

They required a solution that could address the following challenges:

  • Giving end user a choice to use face recognition for marking attendance
  • Accurately detecting the face of each student from classroom pictures
  • Use minimum computation power of a device
  • Reduce time is taken to get a response in the form of attendance

The Solution: An AI-enabled attendance system with accuracy

The proposed system aims to overcome the pitfalls of the existing systems and provides features such as detection of faces, extraction of the features, detection of extracted features, and analysis of student's attendance. The development team brainstormed on Client's requirement and came up with an optimized solution. Training data in the form of faces of each student was captured and faces were recognized by comparing training data and pictures captured by teachers in the classroom. A Web portal and a mobile application were developed with AI-enabled Face Recognition System.

Key features developed for the solution are as follows:

  • AI-enabled Integrated Web and Mobile application for ease of user
  • High end Face recognition system to mark the attendance of students in a classroom
  • Quick response to verify and validate attendance
  • Optimum use of computation power of a device

The Results: Effortless attendance marking with less user interaction

The end product delivered to Client gave good accuracy. The overall process of attendance marking was made effortless with less interaction of the user. This is one of the best examples of how Artificial Intelligence can help in solving challenges existing in the conventional domain.

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