A package designed to predict static pose and detect falls with 2D RGB Camera in well lit indoor environments.
Project description
AI Posture Monitor
This project introduces an innovative, cost-effective solution for real-time activity monitoring of elderly individuals. By leveraging the MediaPipe pose estimation model, fuzzy logic, and finite state machines, the system can reliably track individuals, recognize static postures (standing, sitting, lying), and detect transitions, particularly focusing on falls.
GITHUB: https://github.com/pat2echo/
Features
- Real-Time Activity Monitoring: Tracks and analyzes movements continuously.
- Pose Detection: Identifies key postures**: standing, sitting, and lying down.
- Fall Detection: Detects falls with minimal false alarms.
- Fuzzy Logic Analysis: Utilizes fuzzy logic for accurate movement interpretation.
- User-Centric Design: Tailored for elderly individuals living alone.
- Environmental Adaptability: Functions effectively in well-lit indoor settings.
- Scalable and Cost-Effective: Affordable solution for diverse applications.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file ai_posture_monitor-0.0.7.tar.gz.
File metadata
- Download URL: ai_posture_monitor-0.0.7.tar.gz
- Upload date:
- Size: 31.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.0.1 CPython/3.12.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
6ed3477723b79cc5762bf4c03adb9881e1d24e98c82a97ef2bf2f9a3ad1d6b89
|
|
| MD5 |
ebab1bb735b633a6dd33b2670729daf1
|
|
| BLAKE2b-256 |
922487677e1fe3c0f4a929b239204f11c104b600ea91e1eae30c1b4901a2dc31
|
File details
Details for the file ai_posture_monitor-0.0.7-py3-none-any.whl.
File metadata
- Download URL: ai_posture_monitor-0.0.7-py3-none-any.whl
- Upload date:
- Size: 32.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.0.1 CPython/3.12.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
cbe309452f5f62c4921aeae7d4facfa45334862cee2c6c016f75d4e5b4fe1999
|
|
| MD5 |
75c97a3a2392cdd08088ca74eb8ba0a6
|
|
| BLAKE2b-256 |
a2686ca156d22d2c832e5e152494197f41688528b4b1a69e5023f6dc1be14cf0
|
