Animal Detection for Road safety using Deep Learning

Abstract

Over the years, Accidents due to animals crossing the road at unexpected moments have still been a significant cause of road death. Roads near the forest are dark and dense; hence drivers cannot spot the animals clear. Truck drivers face issues due to blindspot regions. This paper proposes a model that can efficiently detect the animals and alarm the driver. Using Machine learning - A deep learning algorithm, we are segregating the animals with the help of a vast open-source dataset. Using convolution neural networks, the model will predict the object for every image frame received from the Live Camera. If the machine marks an object as an animal, the system gives an alert of 3 seconds to make the driver conscious about the approaching animal. This model doesn't stop with few animals as the dataset is open-sourced the variety of animals detection keep increasing. The model gives 91% accuracy.