Macula is a web-based application designed to monitor student engagement in real-time using computer vision. The platform automates attendance tracking, enhances participation through gamification, and offers real-time feedback to educators.
- Visual Studio Code: A lightweight and powerful source code editor with built-in support for JavaScript, TypeScript, and Node.js.
- MERN Stack:
- MongoDB — Document database
- Express.js — Node.js web framework
- React.js — Client-side JavaScript framework
- Node.js — JavaScript web server
- Postman: Used for testing the API endpoints, ensuring the robustness of the application.
- Figma: Utilized to create UI components and mockups for Macula, enabling collaboration and feedback during the design process.
- face-api.js: Built on top of TensorFlow.js, used for face detection, recognition, and landmark detection. The algorithm extracts face descriptors and compares them to reference data to determine similarity.
- Python Script: Real-time engagement monitoring using facial landmarks and computer vision techniques. The script tracks eye and mouth movements, head pose, and engagement status, storing the data in a MongoDB database.
- Real-Time Face Recognition: Implemented using
face-api.jsfor live video streams. - Engagement Monitoring: Tracks student focus, distraction, and participation levels during sessions.
- Automated Attendance Tracking: Monitors and records attendance without manual input.
