Mining

The application of IoT to geological analysis for identifying economic mineral deposits more accurately with quicker turnaround is being developed through analysis of data of equivalent economic mineral deposits matched to the data of potential greenfield sites supporting a higher order of discovery and accuracy.

 Analysis of potential exploration areas with data sets of known economic mineral deposits assists in expediting scaled area analysis.  The benefits improve exploration risk in improving the outcome of geological field investigation with historical records and application layered advanced visualisation from remote locations delivered to smart devices anywhere.

The use of machine learning to refine targets generated from allied applications analysing historical data sets and real-time analyis in a common shared platform has potential for more effective defined target locations for field management and targeted drilling loications.  

IoT technology can represent GIS location audit and monitored assay results as source data for machine learning applications designed to deliver multi-mineral prospectivity mapping. 

Data visualisation produces a meaningful topological and geological representation of target locations where this output of layered systems integrating artificial neural networks, support vector machine, logic regression in random forest and adaptive boosting for analysis of economic mineral possibilities defining a prospectivity map and spatial dataset targeting exploration areas.

When previous exploration data is added and modelled in system data analytics new hypotheses are more easily created from the interpretation of disparate common digitised data sets held in stakeholder and public storage that delivers a valuable resource for mining professionals and industry knowledge.

Please share those initiative you have thought through and any ideas this endeavour has created here.