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Post Crash
Use Case
Better Rescue Chain
Basic information such as number of occupants, type of occupants and seating position of occupants from before an accident happened, can already help the rescue team to have a faster and better information on what they need to prepare for.
By detecting occupant pose before crash and combining it with crash impulse sensing, even injury estimations are possible which can help the rescue team to get prepared even better. Signs of live and movement help them to understand the severity of injuries even before they arrive. Every second can count.
How does OMS improve the rescue chain?
Ecall systems are mandatory in every car in Europe – reporting accidents directly to the central rescue number. However a first verification on severity of crash still is a crucial element to improve this system – avoid unnecessary trigger of the rescue chain, but trigger the rescue chain as fast as possible with correct information when necessary. Occupant monitoring can contribute to this goal in different ways. Early information on crash severity, likely injuries and health status after crash are important info for emergencies to prepare the right steps and safe lives.
What is occupant monitoring?
Occupant monitoring is providing information about any occupant in the car. While already in the past there have been different sensor technologies for this (i.e. weight sensors) a large focus today is on getting information from cameras by means of computer vision and artificial intelligence. Cameras are being used to extract information like weight, height, body pose, gender, age, emotion, health status and more.
How does it work?
Continuous occupant monitoring already includes the important number of patients. Pose information combined with crash sensing from AD and safety systems can help to estimate injuries of occupants. If the occupant monitoring camera after the crash is still operational, pose information can be used to assess signs of injury and health status.