This study aims to enhance elderly fall detection systems by using the YOLO (You Only Look
Once) object detection algorithm with pose estimation, improving both accuracy and …

In elderly society, the falling of the elderly inside the house is the one of the causes of injury
or death to the elderly. It negatively affects both the family and the elderly themselves …

Human falls refer to a sudden, accidental, unintentional, involuntary, and traumatizing action
of a person losing stability and ending up lying down (often on the ground). These incidents …

Social isolation and loneliness are subjective measures related to the feeling of distress and
discomfort for disabled and elderly people. Currently, computing platform offers a smart …

This work introduces a fall detection system using the YOLOv5mu model, which achieved a
mean average precision (mAP) of 0.995, demonstrating exceptional accuracy in identifying …

Automated identification of human activities remains a complex endeavor, particularly in
unique settings like temple environments. This study focuses on employing machine …

As people age, the frequency and impact of falls among the elderly continue to escalate,
presenting significant health and mobility risks. Efficient detection and immediate response …

The You Only Look Once (YOLO) algorithm is used in this research to demonstrate a
sophisticated human activity detection system integrated with real-time applications …

This project, introduces a user-friendly and efficient system to detect unusual activities in
classrooms. By leveraging Python, YOLOv8, OpenCV, Face recognition, Haar Cascade …