IRS22 is based on the same technology of deep learning and image recognition that is tested and highly scalable, developed by a team of researchers from the University of Washington in collaboration with the Allen Institute for Artificial Intelligence and Facebook AI Research</a > which allows to analyze billions of daily images and videos.

The ErInformatica team has extended and engineered the image recognition technology in a product suitable for real-time analysis of video flows in heterogeneous contexts.

  • Large library of objects already trained for recognition
  • Possibility to train the system to recognize categories of objects not included in the initial preset
  • Real time processing capacity
  • Automatic generation
    • Alarms
    • Statistics


Through the image recognition technology, the system can identify objects not allowed (in specific analysis areas) triggering the generation of a real-time alarm, which can be sent to third-party systems.
The system is able to analyze the presence of one or more types of objects in a specific area. This analysis can be historicized for statistical purposes.

As an example shown in the image, suppose we want to analyze a cycle path: the presence of a motorized vehicle in the analysis area generates an alarm.



Users analysis in ski area

It is possible to define logics to analyze the use of a ski area in order to increase safety on the slopes and, consequently, to trigger specific alarms when one of the following danger situations occurs:
  • User (skier or snowboarder) in a non-admitted area (let us suppose off-piste)
  • User (skier or snowboarder) on the track beyond the guaranteed time (suppose the evening time, the alarm can be propagated to the snowcat drivers in order to prevent a possible collision)
  • Motorized vehicle on the track during track opening hours (let us suppose a snowmobile that intends to drive one the track during opening hours)
  • User with unsuitable equipment (we assume bob or sled) on the track
As defined for the winter season, it can be replicated for the summer season if the slopes are used as downhill trails or other sporting activities for which you want to ensure safety on the tracks.

Analysis of industrial environments

It is possible to define analysis logics in real time due to the existence of work environments in which there is a risk deriving from the presence of maneuvering areas dedicated to operating vehicles.
As an example, we report some contexts for which IRS22 is applicable
  • Heavy vehicle unloading / loading areas
  • Analysis of lanes dedicated to forklifts
  • Analysis of areas restricted to users during specific processing (Steelworks, Foundries, Chemical plants)

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