Machine Learning + Distributed IoT = Edge Intelligence

Internet-of-Things (IoT) systems provide large-scale sensor networks that can be used to monitor and analyze a wide range of physical systems. IoT systems can generate huge volumes of data that needs to be dealt with in a timely fashion. Machine learning (ML) provides compelling techniques for the analysis of large, complex data sets. Many existing machine learning systems operate in the cloud. However, bandwidth, power, latency, privacy, and other issues often require IoT systems to apply ML techniques at multiple levels of the network hierarchy. This paper describes important characteristics of edge intelligence and identifies several important research challenges related to machine learning + distributed IoT systems.