AI Slip and Fall Detection

AI slip and fall detection identifies human falls in real time from standard CCTV camera feeds. Unlike personal fall detection devices requiring the fallen person to activate them, AI camera-based fall detection operates passively and continuously — generating alerts within 3 seconds of a fall event without any action required from the fallen individual.

How the Detection Model Works

Fall detection uses skeletal pose estimation. Models identify body landmarks — head, shoulders, hips, knees, ankles — and track their relative positions across frames. A fall is characterized by rapid downward displacement of head and trunk landmarks combined with subsequent presence at floor level. The model distinguishes intentional floor-level activities (sitting, kneeling) from falls through trajectory analysis — velocity and acceleration profile of the downward movement.

Applications in Saudi Arabia

AI fall detection is deployed across several Saudi environments: hospital and nursing home applications protecting elderly and post-surgical patients; retail applications detecting customer falls on wet floors; and industrial applications detecting worker falls in warehouses, construction sites, and processing facilities where falls carry potentially fatal consequences.