In textile industry, fabric defect relies on human inspection traditionally, which is inaccurate, inconsistent, inefficient and expensive. There were automatic systems developed on the defect detection by identifying the faults in fabric surface using the image and video processing techniques. However, the existing solution has insufficiencies in defect data sharing, backhaul interconnect, maintenance and etc. By evolving to an edge-optimized architecture, we can help textile industry improve fabric quality, reduce operation cost and increase production efficiency. In this session, I’ll share: What’s edge computing and why it’s important to intelligence manufacturing What’s the characteristics, strengths and weaknesses of traditional fabric defect detection method Why textile industry can benefit from edge computing infrastructure How to design and implement an edge-enabled application for fabric defect detection in real-time Insights, synergy and future research directions