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| Format: | Recurso digital |
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Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.15277401 |
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Table of Contents:
- <p>The rise of nuclear families has resulted in less care for the health of the elderly living in private<br>residences. Because of this, they are forced to either abandon their lives of solitude or be admitted to an<br>elderly care facility. This means they have to take care of themselves in every way, including taking their<br>medication and doing their regular tasks. A fall at home or in a care facility could result from this. Serious<br>health problems or even death could result from a fall for which assistance is unavailable. The good cause<br>of assisting the elderly is always bolstered by the application of image processing to detect these falls.<br>Using the idea of a convolutional neural network in image processing, the suggested system offers a<br>reasonable and cost-effective solution to this problem. Frame by frame, the suggested model keeps an eye<br>on the solitary person to make sure they don't fall. The YOLO V8 is being used to assess the region of<br>interest and pixel displacement in data segmentation in order to measure the fall. In addition, the model<br>sends a text message to the doctor, closest relative, and neighbor in an effort to rescue a life. </p>