The objective of this paper is to develop a fall alert and pose detection system using a Raspberry Pi and USB camera, leveraging OpenCV for real-time monitoring. The system aims to enhance safety by detecting falls and specific poses, and triggering alerts to address potential risks promptly.
This paper presents a comprehensive solution for fall alert and pose detection leveraging a Raspberry Pi, USB camera, and the OpenCV Python library. The system is designed to enhance safety by continuously monitoring individuals and detecting fall incidents in real-time. The USB camera captures video frames, which are then processed by the Raspberry Pi using advanced computer vision techniques. By applying a pre-trained pose estimation model, the system identifies and displays whether a person is present in the frame. Additionally, it recognizes specific poses, including fall poses, and triggers an alert mechanism when a fall is detected. This solution aims to provide a cost-effective, reliable, and efficient method for monitoring the safety of individuals, particularly in environments where the risk of falls is significant.
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