Automatic Severity Prediction in Vehicle Accidents

• 

  Canvas of the Business Model

The product we have developed integrates an AI algorithm. This, thanks to a large database of the accidents and involved vehicles, along with the characteristics of the road and other data, such as date and time, helps to predict accidents and detect areas of high accident risk zones. This, in turn, allows public administrations to take different measures to avoid accidents: from urban improvement of the road, to predictive methods (send to police officers, establish controls and radars, signaling, etc.) and reactive methods (ambulance, police) if the accident could not be avoided.

The number of traffic accidents with and without fatalities is high in the UK. Every year around 1700 people die in car accidents, and almost 24,000 are seriously injured. It is a social problem that not only affects the injured and their families, but also insurance companies and the public administration, which has to bear the serious costs derived from them. From repair of roads and infrastructure, to health costs and derived from police action.

Built With

• python
• sklearn