Road Accident are a major cause of death worldwide leading to around 10.25 lakh deaths and 5 crores injuries ever
year. Road accidentsare extremely common. If you live in a sprawling metropolis like we do, chances are that we have
heard about, witnessed, or even involved in one. Therefore, a system that can predict the occurrence of traffic
accidents or accident-prone areas can potentially save lives. Although difficult, traffic accident prediction is not
impossible. Accidents do not arise in a purely stochastic manner; their occurrence is influenced by a multitude of
factors such as drivers physical conditions, car types, driving speed, traffic condition, road structure and weather.
Paper is a deep learning python dynamic Routine maker which is designed to give the user a better
understanding with the next day Traffic and help user to fulfill his/her sleep. Our mode Consider the following
inputs speed, traffic condition, crash counts, road structure and weather to less obvious factors such as national
holidays, the moon cycle and selective attention. Fortunately, several of such accident records are publicly
available. Various municipal and national government in the UK have made available rich datasets of Road
Traffic Accidents (RTA) and their associated factors. By exploring this government datasets and external data
sources, we aim to discover patterns that predict with high accuracy tells road accident to happens.
Software And Hardware