Computer Vision Based Monitoring System for Flotation in Mining Industry 4.0

In the mineral processing industry, specifically in froth flotation, the extraction of detailed information from bubble images is imperative for effective monitoring of the flotation process and its associated production indicators. This study delves into a range of semantic segmentation methods and algorithms, notably including YOLO, Watershed, and Thresholding, to accurately process these images. Our investigation leads to the proposal of an innovative cloud-based segmentation architecture, seamlessly integrated with the Internet of Things (IoT). This integration not only enhances the segmentation process but also supports a comprehensive monitoring application, offering a significant advancement in the real-time analysis and optimization of the flotation process. The article presents an empirical comparison of the segmentation methods and demonstrates the efficacy of the proposed cloud-based system in a practical industrial setting.