ABSTRACT
We experience a lot of targeted advertisements while browsing the internet, which has been made possible using state-of-the-art data mining and machine learning techniques. However, these highly targeted advertisements are yet to use the oldest medium of promotion – outdoor advertisement. The key problem faced by advertising agencies in this digital age is the identification of the target audience. With the identification of high-priority targets in a timely manner, we can increase the reach by ensuring a high level of personalization. We present a novel algorithm and approach using convolutional neural network and deep learning, which works with digital billboards, changing the advertisements as per the target group’s preferences. Our approach is to identify the car’s make and model by classifying the car’s category, thus getting an insight into the type of consumer. Hence by displaying proof motional material only to the targeted audience, we aim to reduce the air time of the advertisement while increasing the efficacy.
