Mind Master is an AI-powered platform designed to enhance the learning experience by dynamically adjusting study content based on the user's real-time emotional expressions.
- Upload Study Materials: Users can upload documents, presentations, and other educational resources to the platform.
- AI-Based Emotion Recognition: Using advanced computer vision techniques, Mind Master analyzes the user's facial expressions through the webcam during study sessions.
- Dynamic Content Adjustment: The AI adjusts the presented content in real-time, modifying the complexity, format, or focus based on detected emotions .
- Enhanced Learning Experience: Personalized content suggestions help keep the user motivated, focused, and better able to understand complex materials.
- Upload Content: Users upload their study material (PDF, PPT, etc.) to the portal.
- Emotion Detection: While the user studies, the AI uses the webcam feed to continuously monitor their facial expressions.
- Content Analysis: The AI analyzes the uploaded study materials and breaks them down into manageable sections or key points.
- Dynamic Adaptation: Based on the detected emotional cues, the platform adjusts the content, offering simplified explanations, deeper insights, or alternative formats (e.g., visual aids, summaries).
- Clone the repository
- Install dependencies
- Run the application
- Upload your study material: After launching the application, upload your study materials in supported formats.
- Enable Webcam Access: Ensure you grant access to your webcam for real-time emotion tracking.
- Begin your study session: As you study, the AI will observe and adjust the content based on your emotional responses, offering real-time feedback and content adjustments.
We will update later after first version of our website
- Backend: Python, Flask
- Frontend: HTML, CSS, JavaScript (React)
- AI Model: Facial emotion recognition and natural language processing (NLP) for content analysis
- Database: PostgreSQL for storing user data and study materials
- Deployment: Docker, AWS/GCP
We will soon look at it