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Healthcare

Healthcare Patient Safety

LinkerVision turns a hospital's existing camera network into a 24/7 VLM-based patient-safety system. On live feeds it detects patient falls in rooms, corridors, and common areas and patients signaling distress by waving or gesturing for help, so staff can respond immediately, and it continuously watches for early-stage fire and smoke across the facility — complementing point sensors that only trigger once smoke reaches them.

VLM output

A thermal (infrared) camera monitors a single person sitting on the edge of a bed in a dark room, who leans forward and reaches toward a bedside table or rail. Over the frames the person moves progressively lower and further to the right, ending face-down and slumped over the edge of the bed with their body partly out of the bed area, with no other person present.

  • Fall Risk DetectedYes
  • Patient Out Of BedPartial
  • Bed Exit AttemptYes
  • Person Count1
  • Caregiver PresentNo
  • PostureSlumped Forward
  • Unattended PatientYes
  • Alert LevelHigh
  • Lighting ConditionThermal/Dark

Customer challenges

1

Patient falls are a leading cause of injury and liability and often occur unwitnessed, yet constant staff observation isn't feasible; patients may be unable to reach a call button, and staff can't watch every room continuously; and fire in a hospital is high-risk with vulnerable, hard-to-evacuate patients, while point detectors can be slow in large or compartmentalized spaces.

Customer benefits

Faster response with reduced injury severity, fewer fall-related complications and claims, and coverage of unwitnessed areas; a safety net beyond call buttons with wider coverage and no extra staff; and earlier fire warning for safer evacuation, protecting patients and assets — all using existing cameras.

Key features

Incident Detection — Person Fall

Detects a person falling and raises an incident alert.

Distress Monitoring (waving)

Detects people waving for help or showing signs of distress.

Fire & Smoke Detection

Detects fire and smoke early in monitored areas.

Before & after

Before Falls discovered only on rounds or when a patient calls out, with delayed response and unclear cause; distress noticed only on rounds or if a patient reaches the call button; and fire detected only after smoke reaches ceiling sensors or is seen by staff. After — with Linker AI Nexa A fall triggers an automatic alert to the nursing station the moment it happens, with a timestamped clip; distress gestures are flagged live to staff for immediate attention; and smoke or flame is flagged at the source within seconds, with location pinpointed.