Deeply integrating Computer Vision, Pose Estimation, and Multimodal Health Risk Recognition algorithms, this feature constructs an intelligent early warning system designed for high-risk behaviors and sudden health events. The system analyzes individual behavior patterns and physiological manifestations in real-time from video or images. It precisely captures high-risk behaviors such as sudden posture changes during falls or prolonged stillness indicating abnormal retention. Simultaneously, by analyzing visual cues like facial microcirculation changes, abnormal skin color, and decreased limb coordination, it assists in identifying precursors to sudden diseases such as heart attacks and strokes. Leveraging temporal behavior modeling and risk assessment models, the system effectively distinguishes between daily activities and potential dangers. Once an anomaly is detected, it immediately triggers a multi-level warning mechanism, notifying family members and caregivers via APP push, SMS, and voice broadcasts. It synchronously transmits anomaly footage, risk type, and location information. This provides 24/7, unobtrusive, and precise safety protection for high-risk groups like the elderly living alone and chronic disease patients, realizing a closed-loop health management system that shifts from passive response to active prevention.
