incontinence_alert_analysis

Visual AI incontinence detection analyzes uploaded images or videos of lower body areas to identify damp clothing and abnormal excretion indicators. It automatically generates structured alert levels, caregiver warnings, and care suggestions to reduce delayed response times.

To set up automated wet clothing alerts, upload a clear video or image of the infant's lower body area and provide your open-id. Running the incontinence analysis script processes the media and returns structured alert levels and care warnings.

Yes, the incontinence detection system supports both real-time continuous monitoring and scheduled inspections. It analyzes visual characteristics and regional changes from camera feeds to instantly detect damp clothing and trigger caregiver alerts.

Yes, a valid open-id is required to run the incontinence analysis script. The open-id is used to save detection results and optionally supports listing historical nursing reports via the cloud API.

Visual AI detection requires clear images or videos of the lower body area to accurately identify damp clothing. Poor lighting, obscured camera angles, or fully covered patients may limit the system's ability to detect excretion signals and trigger alerts.