The rock mechanical assessment of underground mining structures such as drifts and tunnels is still mostly carried out manually and visually by qualified personnel. These procedures are time-consuming, prone to error, and associated with significant risks. At the same time, there is a lack of robust, networked systems that enable continuous real-time monitoring, evaluation, and response to unstable areas. The integration of digital technologies such as sensor systems, artificial intelligence (AI), autonomous robotics, and wireless communication into the complex underground environment has so far been limited.
The MineView project aims to close this gap by developing a holistic, autonomous system for rock condition assessment in underground mining. It combines multi-dimensional data acquisition (e.g. via robots, drones, and sensors embedded in rock), and AI-driven algorithms for interpretation, classification, and early warning.
Project duration: 2025 – 2028
Project partner: