Russian Mines Turn to EDGE-Powered AI for Underground Transport Monitoring

Russian mining operators are deploying an EDGE‑computing AI system to track and manage underground transport even when standard communications fail, boosting efficiency, autonomy and safety.

Russian extraction companies are increasingly integrating IT solutions to monitor their transport fleets. In the complex infrastructure of underground mines, communication outages are more common than reliable connections — but a homegrown EDGE‑computing system is designed to overcome that hurdle.

Currently being rolled out at the Usolsky Potash Plant, the enterprise’s in‑house server can collect and process vehicle data on‑site, including motion‑sensor inputs. This capability allows operators to chart vehicle routes, log stops, generate electronic dispatch requests, minimize downtime and allocate machinery in real time — even when traditional networks go dark.

The EDGE approach not only enhances transport efficiency, resilience and autonomy, but also promises similar gains across other production processes in the mining sector. Usolsky’s plant plans to extend the technology to its surface‑level beneficiation facilities in the near future.

Moreover, adopting this system is expected to lower operating costs and improve worker safety by promptly detecting and averting non‑routine events.