Fall & Accident Detection: Identifies falls, workplace accidents, and impaired individuals through real-time pose recognition based on body posture and movement patterns
Silent Alert via Gesture: Triggers discreet alarms when arms are raised — enabling silent distress signaling.
Pose Estimation Technology: Utilizes AI vision algorithms that detect body keypoints and analyze posture for abnormal movement recognition
Low-Cost, Low-Resource Deployment: Some systems run efficiently on lightweight edge devices, avoiding the need for high-end hardware
Robust & Reliable: Techniques like pose estimation with temporal analysis minimize false positives by buffering multiple frames to confirm fall events
Versatile Monitoring Scenarios: Suitable for industrial, healthcare, transportation, or public environments to enhance personal safety proactively.
Posture Detection is a critical KPI for real-time safety monitoring. By blending pose estimation, gesture-based alerts, and efficient processing pipelines, it enables silent, automated protection without intrusion.