Smart devices, with AI capabilities, at the edge have demonstrated impressive application results. The current trend in video/image analysis is to increase its resolution and classification accuracy. Moreover, computing object detection and classification tasks at the edge require both low latency and high-energy efficiency for these new devices. In this paper, we will explore a novel architectural approach to overcome such limitations by using the attention mechanism of the human brain. The latter allows humans to selectively analyze the scene allowing this limit the spent energy.