Predecting Bus Fitness Using CNN [PBFUC]

Abstract

PBFUC (Predicting Bus Fitness Using CNN) may play a great role to reduce traffic accidents, classification of bus condition. Giving safe roads to people and overcoming from the rate of accidents due to fitness of bus, for all the reasons Bus Fitness Prediction system is essential. We traced that issue of road accidents and settled us to work for reducing road accidents. The most eminent model like Convolutional Neural Network (CNN) is good for classification. In this paper, we proposed a model of Convolutional Neural Network (CNN) for classifying fitness of buses. To classify the condition or fitness of buses we followed two parts – one is feature extraction and another one is classification. These two parts performed good via CNN in our system. In this system, we worked on 2 classes to classify bus fitness- one class is fit buses and another one is unfit buses. So, CNN model played a great role to find a good accuracy and build our system perfectly. We split our total data as 80% for training dataset and 20% for testing dataset there after we achieved evaluate accuracy 80.93% for our CNN model and 84.56% for training accuracy.