Getting the Best of Both Worlds - IoT and Edge Using Hierarchical Inference

Learn about Hierarchical Inference (HI) implementation in IoT and edge computing through this technical lecture delivered by Prof. Jaya Prakash Champati from IMDEA Networks Institute. Explore how Deep Neural Networks (DNNs) can be optimized for both IoT devices and edge computing environments, focusing on achieving high inference accuracy while managing resource constraints. Discover practical applications of HI in Machine Fault Detection using threshold-based algorithms and Image Classification through online learning frameworks. Examine the implementation of Prediction with Experts' Advice featuring continuous action space, and understand how these approaches perform with ImageNet and MNIST datasets. Gain insights into scheduling communication and computation for emerging applications in edge computing systems, Internet of Things (IoT), and Cyber-Physical Systems (CPS) from an expert who has contributed to LTE MAC layer development and received the Marie Skłodowska-Curie Actions fellowship.