Brain on a-board implementation of Neural Networks

In an era of digital computing and software supremacy, analogue computing and electronics often take a back seat. And it is only fair to say that current computers, general applications digital devices, are relied on because of their efficient software rather than hardware. The current flaws in combination with new age computing such as machine learning, and the limitations become glaring especially on devices on the lower end. To overcome this, it becomes necessary to rely on analogue techniques to allow efficient computation and fulfilling the need for dedicated Machine Learning devices capable of similar accuracy as software models. In this paper, with the goal of developing analogue neural networks, the accuracy obtained for on board sensor data was 77% same as a software approach.