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Abnormality Detection

No more false alarms:
Accurately identify human behavior even in obscured conditions like behind fences

Compatibility:
Work with many video management platforms and all IP cameras

Real-time alert:
Send and receive notifications in real time to act upon events just as they occur

Scalability:
Maintain high performance from SMB-scale systems up to tens of thousands of cameras

IronYun’s Abnormality Detection recognizes human behavior such as falling down, crouching, and loitering. Detect people in crowds or those partially obscured by objects or semi-transparent barriers like mesh or chain-link fences. Actions are tracked from the beginning and ending movements in order to reduce false alarms such as from tripping when looking for people falling down.

IronYun AI Video Analytics_Person Fall Detection
IronYun AI Video Analytics_Person Loitering Detection

Example Use Cases

  • Alert shop employees of people standing in front of store windows in order to invite them into the store or contact security for suspicious onlookers
  • Adjust loitering times for different public walkways to manage and control pedestrian traffic across a city or campus
  • Automatically send images of suspicious people late at night on premises to staff, management, and authorities
  • Identify accident-prone areas for public security to monitor more closely
  • Retrieve incidents of employee accidents such falling down stairs for better building and work safety as well as evidence for compensation claims
  • Forewarn staff for cases of theft when people are crouching down or loitering around to steal something in a high-value area