Mining & Resources Group
AIoT for Mining & Resource Operations
Mining and resource operations span large, hazardous, and geographically distributed environments where the location of workers, mobile equipment, extracted material, and operational resources directly affects productivity and safety. AI and IoT can help organizations turn physical movement and operational activity into actionable information for faster decisions. Across surface mining, underground mining, mineral processing and refining, oil sands extraction, and rare earth and critical mineral operations, AIoT systems can support safer workforce coordination, controlled site access, equipment utilization, material movement, and operational traceability. Application-focused AI can help identify abnormal movement, locate critical resources, prioritize field activities, and improve the flow of ore and materials from extraction through processing. These capabilities are particularly valuable where conventional manual coordination becomes difficult because of large sites, remote work areas, complex haul routes, restricted zones, and continuously changing production conditions.
Portfolio Companies under Mining & Resources Group
MineralProcess AI
Concentrators, beneficiation plants, smelters, and refining facilities depend on continuous coordination between operators, maintenance teams, mobile handling equipment, feed materials, intermediate products, and production-critical spares. MineralProcess AI applies AI and IoT systems to help processing and refining organizations improve operational visibility across crushing, grinding, flotation, separation, thickening, filtration, and refining workflows. AI can analyze the movement and location of operators around processing areas to identify unusual activity, prolonged presence in restricted zones, inefficient technician travel, and workflow bottlenecks. This supports better coordination of maintenance crews and faster response to operational interruptions.
Material and inventory coordination presents another major application. AI can help track the movement of ore lots, concentrate containers, intermediate materials, reagents, replacement components, and maintenance supplies between receiving, processing, storage, and dispatch areas. Historical location and movement records can be analyzed to identify material-handling delays, misplaced resources, stock replenishment requirements, and recurring bottlenecks between processing stages. For maintenance operations, location-aware asset and spare-parts workflows can reduce search time and improve readiness for planned shutdowns and unplanned equipment interventions.
RareMetal AI
Rare earth and critical mineral operations require controlled handling of valuable ore, concentrates, intermediate products, specialized processing equipment, and scarce maintenance resources. RareMetal AI uses AI and IoT systems to support operational coordination across extraction, beneficiation, separation, refining, storage, and material-transfer activities. AI can analyze the movement of workers and mobile equipment around extraction and processing areas to identify unusual access patterns, inefficient travel, restricted-area entry, and potential conflicts between personnel and material-handling equipment. These capabilities can help site managers coordinate work around high-value processing areas and maintain better control over operational zones.
Material accountability becomes particularly important when production involves high-value concentrates, separated mineral streams, specialty chemicals, and controlled intermediate products. AI can analyze location events and movement histories to identify unexpected material transfers, prolonged staging, misplaced containers, or deviations from established handling routes. Inventory workflows can also help maintenance teams locate specialized components, processing equipment spares, and critical consumables before scheduled interventions. By connecting material movement with operational records, RareMetal AI can support stronger chain-of-custody practices, more efficient stock management, and improved readiness across critical-mineral processing operations.
ExtractInd AI
Oil sands and other resource extraction operations involve extensive field areas where personnel, heavy equipment, extraction machinery, mobile processing units, work crews, and material-handling resources must be coordinated across continuously changing work zones. ExtractInd AI applies AI and IoT systems to help operators manage movement and resource allocation across mining faces, extraction areas, haul routes, overburden operations, stockpiles, and processing interfaces. AI can analyze worker and equipment movement to identify unsafe interactions, route deviations, prolonged equipment idle time, and congestion around active extraction zones. This can help supervisors coordinate field activities while maintaining clearer separation between personnel and large mobile machinery.
Production continuity also depends on knowing where specialized equipment, replacement components, tools, and extraction-related supplies are positioned. AI can use historical movement and location information to identify frequently relocated resources, recurring equipment bottlenecks, and inefficient staging practices. Location-aware inventory workflows can help field teams locate critical spares and consumables closer to planned maintenance activities, while material movement records can support coordination between extraction, hauling, stockpiling, and downstream processing. These applications can reduce unnecessary field travel and improve utilization across geographically dispersed resource operations.
UndergroundMine AI
Underground mining requires precise knowledge of who is below ground, where mobile machinery is operating, and how personnel move through shafts, declines, drifts, stopes, and designated refuge areas. UndergroundMine AI uses AI and IoT systems to support workforce coordination and access decisions in environments where visibility is constrained and operational conditions can change rapidly. AI can evaluate personnel movement through underground work areas to identify unusual dwell periods, unexpected route changes, personnel entering restricted headings, or interactions between workers and heavy mobile equipment. These insights can assist control rooms and shift supervisors with evacuation coordination, work-area verification, and safer allocation of crews.
Operational efficiency also depends on locating bolters, LHDs, utility vehicles, drilling equipment, tools, and critical maintenance items without unnecessary travel through the mine. AI can analyze equipment utilization and movement histories to identify idle assets, recurring delays, and inefficient equipment allocation. Location-based inventory workflows can help crews find replacement components, consumables, and emergency resources at the required underground staging point, reducing search time and supporting faster maintenance response.
SurfMine AI
Surface mining operations coordinate people, haul trucks, excavators, loaders, drilling equipment, blasting crews, and maintenance resources across expansive open-pit environments. SurfMine AI applies AI and IoT systems to help mine operators understand where personnel and mobile equipment are operating and whether movements align with planned production and safety procedures. AI can analyze personnel movement around haul roads, loading faces, crusher areas, blasting exclusion zones, and maintenance locations to identify unsafe proximity, unexpected dwell times, route deviations, and congestion between mobile assets and workers. Location-aware workflows can also help supervisors coordinate shift changes and confirm that personnel have cleared designated blast zones before controlled activities proceed.
Equipment and material coordination can extend from haulage fleets to high-value attachments, drilling assets, fuel equipment, and maintenance items. AI can identify underutilized equipment, abnormal movement patterns, and recurring delays while location data helps crews find required resources across large pit and stockpile areas. These capabilities support safer dispatching, faster field response, and more predictable mine production.
Building the Future of Industrial AI and IoT for Mining & Resources
For more than three decades, GAO Group of Companies has invested heavily in R & D of industrial IoT. Since generative AI was proven useful in industrial applications, we have been developing AI and IoT technologies, and we have founded Aperture Venture Studio to build, launch, and scale next-generation AI and IoT companies for various industries.
Aperture has been able to attract top AI and IoT technical experts, entrepreneurial and operational executives, influential investors and industry leaders as corporate partners.
Furthermore, we have developed a successful TekSummit and Aperture Ventures Summit to discuss advanced topics on AI and IoT.
As a result, we have built diversified ecosystems and vibrant technical communities for AI and IoT.
To address the enormous and fast-rising demands of AI and IoT in Mining & Resources, we have created Aperture Venture Studio.
Join Aperture Venture Studio
We welcome:
- Advisors, co-founders, founding members and prospective employees
- Strategic, venture, angel, and institutional investors
Let’s work together to build the future of AI and IoT for Mining & Resources.