Russia’s leading gold and diamond producers are embracing technologies that, until recently, were associated primarily with the world’s largest tech companies. Neural networks are now optimizing flotation processes, monitoring haul truck drivers—even through sunglasses—and predicting where valuable ore lies beneath the surface. Mining leaders Polyus and ALROSA have unveiled the latest results of their artificial intelligence initiatives.
One of Polyus’ flagship developments is an in-house platform called Digital Flotation, designed to optimize one of the most critical stages of mineral processing. The AI system continuously monitors flotation froth stability in real time—a key factor that directly affects gold recovery rates.
The company’s use of AI extends well beyond mineral processing. Polyus geologists employ machine learning models to predict ore lithology using X-ray fluorescence (XRF) drilling data. Another AI model analyzes geological datasets to identify prospective ore zones and support mineral exploration efforts.
At the Sukhoi Log project, Polyus has also introduced AI-powered video analytics into haul truck cabins. Forty SITRAK trucks have been equipped with monitoring systems featuring Driver Monitoring System (DMS) cameras and additional sensors installed inside and outside each vehicle. The technology detects unsafe behavior, including unfastened seat belts, lapses in attention, and early signs of driver fatigue. One of the system’s standout capabilities is its ability to accurately track a driver’s gaze—even when the driver is wearing dark sunglasses.
ALROSA is also expanding its use of artificial intelligence, with a particular focus on improving safety in open-pit mining operations. The company is developing an AI model to predict hazardous gas accumulation in its pits. Instead of relying solely on direct gas measurements, the system analyzes indirect indicators such as air temperature, wind direction, and wind speed collected by on-site weather stations. Although the model has not yet achieved complete accuracy in forecasting the timing and dissipation of hazardous emissions, ALROSA is continuing to refine the technology in collaboration with the Obukhov Institute of Atmospheric Physics of the Russian Academy of Sciences.
In addition, both companies are introducing AI assistants powered by large language models for internal operations. These systems search corporate knowledge bases, retrieve relevant information, and generate tailored responses to employee queries, significantly reducing the time spent on routine information searches.
Artificial intelligence in Russia’s mining industry has moved beyond experimental pilot projects to become an operational tool. From flotation optimization and geological exploration to mine ventilation safety and driver monitoring, AI is increasingly being deployed wherever worker safety and metal recovery efficiency are at stake.
Source: @nerzhavey
Image: ALROSA
