Industrial Distributed Edge Architecture over Machine Intelligence for Local Learning

The Industrial Distributed Edge Architecture over Machine Intelligence for Local Learning (IDEA-MILL) research project addresses the key challenges in future hyper-connected industrial systems to deliver innovative solutions, which are prepared to handle the extremely large data volumes collected from multiple heterogeneous sources, make adequate inference, and provide timely response. Our proposed distributed edge architecture diffuses machine intelligence across the network by bringing more critical and demanding applications closer to smart machines while moving lightweight data and local learning outcomes to the cloud for enterprise-level analytics. Our expected key scientific results are in developing efficient, flexible, and scalable methods that automate model training processes as well as control storage, computing, networking, and radio resources to minimize the associated costs and latencies.