Abstract

The Internet of Things (IoT) is transforming industries by enabling devices to gather and share data. However, IoT devices often face limitations in processing power, storage, and energy consumption, restricting their ability to make complex decisions in real time. To address these challenges, cloud-assisted edge AI combines the advantages of edge computing and cloud-powered machine learning models, enabling IoT devices to make intelligent decisions at the edge while leveraging cloud resources for more complex processing tasks. This paper explores the integration of edge AI with cloud assistance, demonstrating how this hybrid approach enhances decision-making capabilities in IoT devices. The paper examines key concepts, the architecture of cloud-assisted edge AI systems, application areas, and the benefits of combining edge and cloud computing. Furthermore, challenges such as latency, data privacy, and integration issues are discussed, alongside future directions for this technology in IoT applications.