ConductVision Enterprise
Fall Detection
Designed to detect falls and route alerts to your team. Available for pilot.
Fall Detection uses pose-estimation models to identify the rapid vertical-to-horizontal body transitions characteristic of fall events, distinguishing them from normal activities like sitting down, bending, or lying on a couch. The system is designed to route an alert when a fall is detected, supporting response workflows in elderly care, assisted living, and industrial safety. Unlike wearable-based solutions, camera-based detection requires no device on the person and works for anyone within the camera field of view, visitors, staff, and residents alike.
How it works
Fall Detection in three steps
Connect Room and Hallway Cameras
Install cameras in common areas, hallways, bathrooms (privacy-mode compatible), and high-risk zones. The system works with existing IP cameras and supports privacy-preserving skeleton-only processing where full video is not appropriate.
Pose Estimation and Fall Classification
A real-time pose-estimation model tracks body keypoints frame by frame, building a temporal sequence of posture states. A fall classifier analyzes the velocity and trajectory of the transition from upright to ground-level, filtering out normal activities like sitting or crouching.
Route Alerts for Response
When a fall is confirmed, alerts are dispatched to designated caregivers, nursing stations, or monitoring centers with the camera location, a snapshot or skeleton-only image, and the timestamp. If no response is acknowledged within a configurable window, the alert escalates.
Features
Rapid Fall Detection
Identifies fall events by analyzing the speed and angle of body posture change. The temporal model distinguishes sudden collapses from gradual position changes.
Activity Discrimination
Differentiates falls from normal activities, sitting down, bending to pick up objects, lying on furniture, exercising on the floor. Reduces false alarms that erode trust in alerting systems.
Skeleton-Only Privacy Mode
Processes video as anonymous skeletal keypoints only, discarding all pixel data. Alerts include stick-figure visualizations instead of photographs, suitable for bedrooms and bathrooms.
Post-Fall Immobility Monitoring
After detecting a fall, the system monitors whether the person regains mobility. Extended immobility triggers escalated alerts, as prolonged time on the ground correlates with worse outcomes.
Multi-Person Tracking
Tracks multiple individuals simultaneously within a single camera view, detecting falls for any person regardless of occlusions from furniture or other people.
Escalation Chains
Configurable alert routing sends initial notifications to nearby staff, then escalates to supervisors and emergency contacts if the alert is not acknowledged within defined time windows.
Historical Fall Analytics
Logs all detected falls with location, time, and context. Facility managers can identify high-risk areas, peak fall times, and recurring patterns to guide preventive interventions.
Use cases
Assisted Living Facilities
Residents in assisted living may be alone when a fall occurs. Camera-based detection can notify on-duty staff so a fall does not wait for the next scheduled check.
healthcaresenior living
Hospital Patient Monitoring
Hospitalized patients, especially those recovering from surgery or on sedating medications, are at elevated fall risk. Room-mounted cameras in skeleton-only mode can alert nursing staff without compromising patient privacy.
Home Care for Aging in Place
Older adults living independently face fall risk without on-site staff. A camera system in key rooms can alert family members or remote monitoring services, enabling aging in place with an additional safety layer.
healthcaresenior living
Industrial Workplace Safety
Workers on elevated platforms, ladders, and scaffolding face fall hazards. Camera-based detection can provide an alert independent of whether the worker is wearing a personal fall-arrest system, covering visitors and contractors as well.
manufacturingconstructionenergy
Retail Slip-and-Fall Monitoring
Customer falls on wet floors or cluttered aisles call for a fast staff response. Detection can prompt that response and generate timestamped incident documentation for risk management.
retailhospitality
Public Transit Station Safety
Falls on escalators, platforms, and stairways at transit stations require rapid response. Automated detection can alert station personnel immediately, supplementing the coverage that human monitoring of dozens of camera feeds cannot maintain.
transportationsmart city
Technical overview
- Models
- YOLOv8-Pose with temporal LSTM fall classifier; trained on synthetic and real fall datasets
- Input formats
- RTSP, ONVIF, MP4, HLS, MJPEG
- Output formats
- JSON, MQTT, Webhooks, HL7 FHIR (healthcare integration), CSV
- Edge support
- NVIDIA Jetson (Orin/Xavier), Intel NUC, any x86 with CUDA-capable GPU
Accuracy and latency are measured against your footage and cameras during pilot scoping; we publish figures only with the conditions they were measured under.
Related capabilities
People Detection
Occupancy intelligence from the cameras you already have. Available for pilot at any scale.
Behavioral Analytics
Loitering, aggression, crowd surges, and abandoned objects, anomaly detection grounded in behavioral science. Available for pilot.
Crowd Analytics
Density estimation, flow analysis, and surge detection for any gathering. Available for pilot at venue and city scale.
Evaluate Fall Detection on your footage
One prioritized outcome, your cameras, a structured results review.
