https://github.com/aarambhtech/exam-cheating-detection
AI-powered online exam proctoring system that detects suspicious activities using computer vision. Tracks eye movements, face presence, multiple faces, and talking during exams with real-time alerts and dashboard.
https://github.com/aarambhtech/exam-cheating-detection
ai-education ai-monitoring ai-security cheating-detection computer-vision deep-learning education-tech exam-proctoring exam-security eye-tracking face-detection mediapipe online-assessment online-exams online-learning opencv proctoring-system python-flask-dashboard remote-learning student-authentication
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AI-powered online exam proctoring system that detects suspicious activities using computer vision. Tracks eye movements, face presence, multiple faces, and talking during exams with real-time alerts and dashboard.
- Host: GitHub
- URL: https://github.com/aarambhtech/exam-cheating-detection
- Owner: AarambhTech
- License: mit
- Created: 2025-05-16T10:23:14.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-05-18T08:53:44.000Z (about 1 year ago)
- Last Synced: 2025-06-17T08:07:33.987Z (about 1 year ago)
- Topics: ai-education, ai-monitoring, ai-security, cheating-detection, computer-vision, deep-learning, education-tech, exam-proctoring, exam-security, eye-tracking, face-detection, mediapipe, online-assessment, online-exams, online-learning, opencv, proctoring-system, python-flask-dashboard, remote-learning, student-authentication
- Language: Python
- Homepage:
- Size: 43 KB
- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# AI-Powered Online Exam Cheating Detection System
A computer vision system that detects suspicious activities during online exams using webcam footage.
## Features
- **Face Presence Detection**: Identifies when student's face is not visible
- **Eye Movement Tracking**: Detects excessive eye movements (left/right/up/down)
- **Gaze Analysis**: Monitors direction of eye gaze
- **Mouth Movement Detection**: Identifies potential talking or whispering
- **Multi-Face Detection**: Alerts when multiple faces appear in frame
- **Real-time Alerts**: Flags suspicious activities with timestamps
- **Dashboard**: Visual interface showing detection metrics and alerts
- **Object Delection**: Object Detection: Detects prohibited objects (cell phone, book, etc.).
- **Screen Recoding**: Continuously captures examinee's screen activity
- **Audio Detection**: Monitors for voice/whispering in student's environment
- **Alert Speaker**: Delivers real-time verbal warnings via text-to-speech
- **Report Generation**: Creates detailed visual PDF and HTML reports with violations summary, heatmaps, and activity timeline
## Technologies Used
- Python 3.8+
- OpenCV (for computer vision)
- MediaPipe (for face mesh and landmark detection)
- FaceNet-PyTorch (for face detection)
- MTCNN (for face detection)
- Flask (for dashboard)
## Installation
1. Clone the repository:
```bash
git clone https://github.com/yourusername/exam-cheating-detection.git
cd exam-cheating-detection
```
2. Install dependencies:
```bash
pip install -r requirements.txt
```
3. Download pre-trained models (if needed):
```bash
python -c "from facenet_pytorch import MTCNN; MTCNN(keep_all=True)"
```
## Usage
1. Configure the system by editing `config/config.yaml`:
```yaml
video:
source: 0 # 0 for default webcam
resolution: [1280, 720]
fps: 30
recording_path: "./recordings"
screen:
monitor_index: 0 # 0 for primary monitor
fps: 15 # Lower FPS for screen recording
recording: true # Enable/disable screen recording
detection:
face:
detection_interval: 5 # frames
min_confidence: 0.8
eyes:
gaze_threshold: 2 # seconds
blink_threshold: 0.3 # EAR threshold for blink detection
gaze_sensitivity: 15 # pixels threshold for gaze detection
consecutive_frames: 3 # frames for gaze change detection
mouth:
movement_threshold: 3 # consecutive frames
multi_face:
alert_threshold: 5 # frames
objects:
min_confidence: 0.65 # Detection confidence threshold
detection_interval: 5 # frames between detections
max_fps: 5 # Maximum detection frames per second
audio_monitoring:
enabled: true
sample_rate: 16000
energy_threshold: 0.001
zcr_threshold: 0.35
whisper_enabled: false # Enable only when needed
whisper_model: "tiny.en"
logging:
log_path: "./logs"
alert_cooldown: 10 # seconds
alert_system:
voice_alerts: true # Enable/disable voice alerts
alert_volume: 0.8 # Volume level (0.0 to 1.0)
cooldown: 10 # Minimum seconds between same alert
```
2.Run the main detection system:
```bash
python src/main.py
```
3. (Optional) Run the dashboard in another terminal:
```bash
python src/dashboard/app.py
```
4. Access the dashboard at `http://localhost:5000`
## System Architecture
```
exam_cheating_detection/
├── config/ # Configuration files
├── models/ # Pretrained models
├── src/ # Source code
│ ├── detection/ # Detection modules
│ ├── reporting/ # Reporting application
│ ├── utils/ # Utility functions
│ ├── dashboard/ # Web dashboard
│ └── main.py # Main application
├── logs/ # Session logs
└── recordings/ # Recorded video sessions
```
## Customization
You can adjust detection thresholds in `config/config.yaml`:
```yaml
eyes:
gaze_threshold: 2 # seconds of gaze deviation to trigger alert
blink_threshold: 0.3 # eye aspect ratio for blink detection
mouth:
movement_threshold: 3 # consecutive frames of mouth movement
```
## Troubleshooting
Problem: Eye detection working, but not perfect
Solution:
- Ensure good lighting on face
- Remove glasses if they cause glare
- Adjust camera position to be face-level
Problem: Book detection working, but not perfect
Solution:
-
## Contributing
Contributions are welcome! Please open an issue or pull request for any improvements.
## License
MIT License - See [LICENSE](LICENSE) for details.
## ☕ Support the Project
If you find this project helpful, consider buying me a coffee!
[Buy Me a Coffee](https://buymeacoffee.com/aarambhdevhub)