As increase in the number of uses of vehicles followed by increase of accidents due to the lack of knowledge of the road or ignorance of the driver. There is rapid increase in the accident and is has more share in the increasing of mortality. The application is developed to help the people about the area. There are unusual cause for the accident. So, the primary factors that contribute for the accident severity. The scientific approach need to be taken by the RTO to provide the information about the accidental hotspot to the people and department. In this work we have studied the accident occurrence area using the prediction model by considering the previous incident, condition of road with the year. The Xg Boost classifier is used to classify the severity of the accident in three types High, Low, Medium. The Flask web framework is used to represent the model for user friendly. This can be used for the driver to be more conscious and PWD for betterment of the road design and condition based on the estimate obtained by the model.

Accident prediction, Classification, Machine Learning, Flask