Abstract

In this ground-breaking endeavor, we describe an automated skin cancer screening booth that can transform current approaches to early detection. The merging of Raspberry Pi-controlled technology with cutting-edge Artificial Neural Network (ANN) models forms the basis of our groundbreaking breakthrough. The booth uses high-resolution imaging sensors to acquire detailed photographs of the user's skin, which are then analyzed in real-time by an ANN. The ability to identify potentially malignant anomalies in a timely and precise manner is made possible by this combination. In public places, user contact is facilitated by the use of an intuitive touchscreen interface, which ensures both accessibility and convenience of use. The ANN model, trained on a wide variety of data, is very good at differentiating between normal and malignant skin diseases, with the findings being instantly shown on the interface. Beyond its technological capabilities, our technology bears the prospect of broad application, which will turn screening for skin cancer into a preventative healthcare tool available to everyone. This all-encompassing strategy highlights the significance of early detection and argues for a solution that is both scalable and effective at the crossroads of technology and public health.