Multi-Modal Big Data Analyzing Architecture for Industrial Internet of Things

Multi-modal big data analysis has emerged as a vital tool within the Industrial Internet of Things (IIoT). Despite its significance, challenges persist, particularly the absence of an efficient analytical architecture. In this study, we introduce a novel multi-modal big data analysis framework tailored for IIoT. Our approach features a cloud-edge collaborative training solution designed to optimize the training of deep learning models, along with an edge-based rapid reasoning solution for deploying models and facilitating swift inference on resource-constrained devices in industrial settings.