Fall Safe is designed to address fall-related injuries among vulnerable populations by leveraging computer vision and machine learning. The system detects falls in real-time from CCTV footage, analyzing video streams to identify abnormal movements and postures. Alerts are sent to caregivers or emergency services with details about the incident, aiming to improve response times and safety for at-risk individuals.
- Real-Time Fall Detection: Utilizes YOLOv8 for accurate fall detection.
- Integration: Works with existing CCTV setups.
- Alerts: Sends notifications with incident details to caregivers or emergency services.
Contributions are welcome! Please open an issue or submit a pull request if you have improvements or suggestions.
This project is licensed under the MIT License - see the LICENSE file for details.
For any questions or feedback, please contact us at Issues Pages.
Fall Safe is developed by the above contributors. For more information, visit our GitHub repository.
