Generative AI for Consumer Internet of Things: Challenges and Opportunities

Weiwei Jiang, Yang Zhang, Haoyu Han, Jianbin Mu

Abstract: Generative artificial intelligence (AI) is a transformative technology driving the realization of consumer Internet of Things (IoT) systems. This article investigates how generative AI can be leveraged to revolutionize data processing and content generation within consumer IoT networks. The study focuses on deploying generative AI models at the network edge, examining their advantages, including reduced latency, improved bandwidth efficiency, enhanced privacy, and offline functionality. By analyzing specific applications in satellite IoT, maritime IoT, power IoT, and medical IoT, this article highlights the lifecycle of generative AI at the edge, from pretraining and fine-tuning to inference. In addition, this article addresses key challenges in real-world implementation, such as quality control, security, privacy concerns, and scaling compute infrastructure. It concludes by identifying future research directions in areas, such as communication, sensing, computing integration, edge–cloud collaboration, and multimodal learning, with the goal of advancing the practical application of generative AI in consumer IoT systems.

External IDs:dblp:journals/cem/JiangZHM25