Article by R. Colin Johnson: “Artificial Intelligence (AI) is renovating the fast-growing Internet of Things (IoT) by migrating AI innovations, including deep neural networks, Generative AI, and large language models (LLMs) from power-hungry datacenters to the low-power Artificial Intelligence of Things (AIoT). Located at the network’s edge, there are already billions of connected devices today, plus a predicted trillion more connected devices by 2035 (according to Arm, which licenses many of their processors).
The emerging details of this AIoT development period got a boost from ACM Transactions on Sensor Networks, which recently accepted for publication “Artificial Intelligence of Things: A Survey,” a paper authored by Mi Zhang of Ohio State University and collaborators at Michigan State University, the University of Southern California, and the University of California, Los Angeles. The survey is an in-depth reference to the latest AIoT research…
The survey addresses the subject of AIoT with AI-empowered sensing modalities including motion, wireless, vision, acoustic, multi-modal, ear-bud, and GenAI-assisted sensing. The computing section covers on-device inference engines, on-device learning, methods of training by partitioning workloads among heterogeneous accelerators, offloading privacy functions, federated learning that distributes workloads while preserving anonymity, integration with LLMs, and AI-empowered agents. Connection technologies discussed include Internet over Wi-Fi and over cellular/mobile networks, visible light communication systems, LoRa (long-range chirp spread-spectrum connections), and wide-area networks.
A sampling of domain-specific AIoTs reviewed in the survey include AIoT systems for healthcare and well-being, for smart speakers, for video streaming, for video analytics, for autonomous driving, for drones, for satellites, for agriculture, for biology, and for artificial reality, virtual reality, and mixed reality…(More)”.
