MineTRACE: Transparency and Interaction with Artificial Intelligence
The mining industry is a complex area that requires combining geography, chemistry and physics data to explore underground wealth. However, existing prospectiveness systems often provide numeric scores or heat maps, giving very little information to decision makers. MineTRACE was developed to solve this problem with artificial intelligence and interactive design.
The main features of MineTRACE are:
- Sekiz analysis of the main metal: It evaluates prospectiveness for copper, gold, nickel, tungsten, tin, cobalt, tantalum and manganese
- Web-based access: Users via the Internet can query certain locations or regions -** Descriptions based on the body**: Shows geological, geochemical and geophysical evidence behind each outcome
- Natural language interaction: Users can transmit their questions into the system by typing them and results provide insightful
The system accelerates decision making by integrating traditional mineral research methods into the artificial intelligence framework. Researchers and industry professionals can explore opportunities from new sites in the guidance of models trained through past data.
MineTRACE represents a practical example of the use of AI in the mining industry, enabling complex data to be understood by human.