ABSTRACT
As the intelligent transportation system is evolving, the number of vehicles is increasing rapidly; however, the number of accidents is also increasing in the same proportion. Accidents are very common nowadays. Infrastructure is redefining and on-road speed of vehicles is increasing. Accident-prone areas are increasing. Billions of people are losing their life due to accidents. This chapter analyzes the data of India’s 11 states which are accident prone, considering different time zone, and proposes a new system that predicts the accident-prone areas and provides the safest time for traveling along that route. Internet of Things and cloud computing concept are used to gather and process large amount of data generated through real-time scenario. DBSCAN data algorithm with negative sampling is used to train our system to make the best decision based on past experience with the help of Internet of Things. Simulation results show that the number of accidents reduced after applying the proposed concept.
