Abstract
This project presents an intelligent monitoring system that uses computer vision technologies to improve the care of older adults. Various tests were carried out to demonstrate the accuracy and effectiveness of the selected machine learning models, as well as comparisons between the training data used, including different training/test split divisions to determine the best configuration. In addition, a proprietary dataset with 300 videos was created and compared with a subset of NTU RGB+D. The results showed high accuracy and effectiveness in activity detection and tracking.
| Original language | English |
|---|---|
| Title of host publication | 2024 IEEE Colombian Conference on Communications and Computing, COLCOM 2024 - Proceedings |
| Editors | Diana Z. Briceno Rodriguez |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9798331504724 |
| DOIs | |
| State | Published - 2024 |
| Event | 2024 IEEE Colombian Conference on Communications and Computing, COLCOM 2024 - Barranquilla, Colombia Duration: 21 Aug 2024 → 24 Aug 2024 |
Publication series
| Name | 2024 IEEE Colombian Conference on Communications and Computing, COLCOM 2024 - Proceedings |
|---|
Conference
| Conference | 2024 IEEE Colombian Conference on Communications and Computing, COLCOM 2024 |
|---|---|
| Country/Territory | Colombia |
| City | Barranquilla |
| Period | 21/08/24 → 24/08/24 |
Bibliographical note
Publisher Copyright:© 2024 IEEE.
Keywords
- metrics
- models
- neural networks
- preprocessing
CACES Knowledge Areas
- 417A Electronics, Automation and Sound
Fingerprint
Dive into the research topics of 'Intelligent Elderly Monitoring System Using Computer Vision'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver