Data analytics on accident data for smarter cities and safer lives

Analysis of accidents has always been very important to take major decisions. In this paper, analysis of accident data set is done, where the dataset consists of the information related to accidents such as the type of accidents, condition of light during the accident, severity of accident, speed zone, consumption of alcohol involved in the accident etc. The focus is laid on the application of data analytics to predict and reduce the impact of the accidents and uncover the relevant trends by training the system with the past data using decision tree methodology. The major causes leading to the accidents are identified and analyzed using some of the relevant attributes such as alcohol consumption, hit and run cases etc. Some demographic graphs are also plotted to bring out better visual insights.