AI-Driven Edge Computing for Risk Prediction in IIoT Environments

This research presents an industrial risk prediction model for multimodal data based on edge computing, aiming at real-time and efficient industrial site risk prediction. Most AI-driven applications require high-end servers to perform complicated AI tasks, resulting in significant energy consumption in IIoT contexts. This study will discuss intelligent edge computing, an emerging technology that may cut energy usage while processing AI tasks, and how to construct green AI technology for IIoT applications. The study also analyses AI technology, and existing technologies to determine the optimal way for generating risk prediction in the IIOT environment.