The Frontier of Large AI Models in IoT Networks: Challenges and Opportunities.

The integration of advanced Artificial Intelligence (AI) models with the Internet of Things (IoT) is ushering in a transformative phase. Sophisticated AI architectures are demonstrating exceptional performance across perception, decision-making, prediction, and multimodal understanding, promising intelligent and context-aware services in domains such as smart cities, precision agriculture, health monitoring, and industrial automation.However, the adaptation of these potent AI models to resource-constrained, distributed, and latency-sensitive IoT environments remains a significant challenge. The computational and memory requirements of many advanced AI approaches often exceed edge capabilities, necessitating innovations in model compression, edge-cloud collaboration, quantization, and efficient inference. Additionally, inherently decentralized and heterogeneous IoT data raises challenges in fine-tuning, continual learning, and privacy-preserving updates (e.g., through federated and split learning).This Research Topic seeks to investigate the integration of large AI models in IoT networks and address challenges across system design, data modeling, inference, communication efficiency, and deployment. We invite contributions that advance understanding of how modern AI paradigms can be adapted to heterogeneous IoT environments. Interdisciplinary work bridging AI, embedded systems, communications, and edge/cloud computing is encouraged, especially case studies and real-world applications.Topics of interest include, but are not limited to:Efficient deployment of large AI models on edge, fog, or hybrid architecturesModel compression, distillation, and quantization for IoTCommunication-aware training and inference (e.g., federated or split learning)AI methods for time-series prediction or anomaly detectionLarge AI-assisted resource management in IoTPrivacy, security, and energy-efficiency in large AI–IoT integrationCognitive IoT systems powered by advanced AI modelsBenchmarking frameworks and ethical considerations for AI-IoT integrationThrough this collection, we aim to foster scalable, secure, and intelligent IoT infrastructures powered by next-generation AI models. Topic editors: Abdulmalik Alwarafy, Mohammad Hayajneh, Rashid Mirzavand Source: https://www.frontiersin.org/research-topics/74420/the-frontier-of-large-ai-models-in-iot-networks-challenges-and-opportunities