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In industrial restricted areas, automated lines, and warehouse work zones, an unauthorized entry can create an operational risk. This solution uses a 3D camera and human-recognition software to detect entries into a configured area and report events to a higher-level system.
Human safety monitoring solution

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Solution overview

The system captures RGB-D data with an M Series 3D camera. Human-recognition software checks whether a person crosses a boundary within the configured ROI. Detection events can trigger an alarm or another action in the higher-level system.
Restricted-area entry detection workflow

Restricted-area entry detection workflow

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System components

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M4 Pro 3D depth camera

  • Provides 3D information about people moving in the monitored space.
  • Depth resolution: 640 × 480; RGB resolution: 1920 × 1080.
  • Aligns RGB and depth data in both space and time.
  • Can run supported algorithms on the device to reduce the need for an external industrial computer.
M4 Pro human-safety monitoring deployment

M4 Pro deployment for human-safety monitoring

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Intelligent human-recognition software

  • Configure a region of interest (ROI).
  • Detect and report a person crossing the restricted boundary.
Human-safety software ROI configuration
Human-safety software detection results

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Workflow

1

Configure the restricted area

Define the ROI from the site layout and camera field of view, excluding areas that are not part of the detection task.
2

Monitor continuously

The camera captures the restricted area while the software checks whether a person enters or crosses the configured boundary.
3

Report the event

When an event is detected, the system reports it to the higher-level system, which can trigger an alarm, stop operation, or take another configured action.

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Application scenarios

  • Automated production lines
  • Warehouse and logistics areas
  • Hazardous-material storage areas
  • Workshops or laboratories with personnel exclusion requirements

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Performance notes

Original test records report single-frame false-positive and missed-detection rates under ideal laboratory conditions. The test used an open field of view, an unobstructed person within 5 m of the camera, a movement speed below 3 m/s, and good ambient lighting. Actual results depend on camera height, field of view, occlusion, posture, lighting, motion blur, and filter settings.
Adjusting the software filter window changes detection stability and response time. Use results from the target site as the acceptance basis.
This solution detects people entering an area. It does not replace light curtains, emergency stops, interlocks, functional-safety controls, or a site risk assessment. Implement and validate complete safety functions in a system that meets applicable regulations and standards.

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Deployment recommendations

  • Keep the lens clean and check regularly for obstructions in the camera field of view.
  • Validate the system on site before deployment in areas with heavy dust, strong reflections, or other extreme conditions.
  • Revalidate the detection range and response chain after changing the camera position, detection area, or higher-level action logic.