Submitted by: AICA Level2 Batch02
PUNEET SAKHUJA, 506700; PRIYA SHARMA, 430040; PUSHPENDRA AGGARWAL, 400594
## Project Description: Emotion-Aware Attendance System
### Introduction
The Emotion-Aware Attendance System is an innovative application of **Artificial Intelligence (AI)** and **Computer Vision** that goes beyond traditional attendance mechanisms. Unlike conventional biometric systems such as fingerprint or RFID, this system not only identifies the presence of a student but also detects and records their **emotional state** during the session.
### Problem Statement
Conventional attendance systems are:
- Time-consuming (manual roll calls).
- Limited to identity verification without providing insights into student engagement.
- Lacking emotional intelligence, making it difficult for teachers to understand the classroom’s overall mood and learning effectiveness.
This gap inspired the creation of an **AI-driven attendance system** that integrates **facial recognition** with **emotion detection** to create a smarter, more interactive classroom environment.
### Objectives
1. Automate attendance marking through face recognition.
2. Detect and analyze the emotional state (e.g., happy, sad, neutral, angry, surprised, etc.) of each student.
3. Provide teachers with insights into student engagement levels.
4. Minimize errors and increase efficiency compared to traditional methods.
### Technology Used
- **Google AI Studio** and **Gemini API** for facial and emotion recognition.
- **Python/OpenCV** for computer vision and image preprocessing.
- **Database (SQL/Cloud Firestore)** for storing attendance and emotion records.
- **Dashboard/Interface** to visualize real-time attendance and emotional analytics.
### Methodology
1. Capture live video feed using a webcam or CCTV camera.
2. Use face detection to identify students in the frame.
3. Apply emotion recognition models to classify facial expressions.
4. Automatically log the student’s **attendance + emotion status** in the system.
5. Generate reports for teachers on attendance and engagement trends.
### Expected Outcomes
- A fully functional system that marks attendance seamlessly.
- Reports highlighting emotional distribution across the class (e.g., how many students looked attentive, distracted, or stressed).
- Enhanced classroom engagement monitoring for teachers.
- Scalable solution that can be adapted to offices, conferences, and events.
### Conclusion
The Emotion-Aware Attendance System combines the **accuracy of AI facial recognition** with the **human touch of emotional understanding**. By integrating technology with empathy, this project aims to revolutionize classroom management, making learning environments more efficient and emotionally intelligent.