mUni Campus Institute Advanced 5 milestones 100 marks

Facial Recognition Attendance System Using Mobile Camera

Real-world project · AICTE-aligned · AI-graded · Audit-ready certificate

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Milestones

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Core skills

About this project

Facial Recognition Attendance System Using Mobile Camera

Milestones

1. Requirements Analysis and Design

15 marks 10d

Define system requirements, user roles, and design data flow and UI wireframes.

2. Image Capture and Storage Module

20 marks 12d

Develop the module to capture and store multiple classroom images via mobile device.

3. Facial Recognition Integration

25 marks 18d

Implement facial detection and recognition to identify students from images.

4. Attendance Processing and Reporting

20 marks 10d

Automate attendance marking and generate attendance reports from recognized faces.

5. Testing, Documentation, and Demo

20 marks 10d

Test the full system, write user and technical documentation, and present a live demo.

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Upcoming sessions

Session	Window	Enrolled
Minor Project	20 May 2026 to 01 Jul 2026	0

Skills you'll learn

Implementing facial recognition using machine learning libraries Developing mobile or web-based user interfaces Integrating camera functionality with applications Processing and storing image data securely Building RESTful APIs and handling backend logic Testing and evaluating recognition accuracy Creating simple attendance reporting tools

Tools used

Python OpenCV Face Recognition library (e.g.face_recognition or dlib) Flask or Django (backend framework) SQLite or Firebase (database) Android Studio or React Native (if mobile app)

Prerequisites

Introduction to Programming (Python or JavaScript) Basic Machine Learning concepts Database Fundamentals Mobile or Web Application Development basics

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You'll earn — Certificate (PDF)

AICTE-aligned Project Completion Certificate

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AICTE-aligned

Certificate of Project Completion

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Facial Recognition Attendance System Using Mobile Camera

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You'll earn — Digital Badge

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