Research on the Application of a Uav Ecosystem and Artificial Intelligence to the Audit of Mineral Exploitation Activities in Quang Ninh for the State Audit Office of Vietnam

Operational auditing of mineral exploitation is highly complex due to large mining areas, difficult terrain, continuously changing extraction operations, and legal and environmental risks such as boundary violations, over - extraction, and pollution. In the practical context of the State Audit Office of Vietnam (SAV), audit evidence still relies heavily on documentation provided by enterprises, while on - site inspections remain constrained by time, resources, and safety. Quang Ninh Province is a major mining h ub, especially for coal exploitation — accounting for approximately 90% of national coal output — making technology - enabled audit enhancement increasingly necessary. This conceptual/framework paper synthesizes published UAV - surveying, remote - sensing and AI - monitoring studies together with a documented SAV audit case to propose an integrated model combining a UAV ecosystem and artificial intelligence (AI) — multi - sensor UAVs, RTK/GNSS positioning, multi - temporal satellite remote sensing, and AI algorithms (o bject detection, change detection, anomaly detection) — for auditing mineral exploitation activities, together with a step - by - step audit workflow tailored to the SAV for deployment in Quang Ninh. The model is designed to support: (i) license and boundary c ompliance verification; (ii) extraction and stockpile volume estimation using DEM/DSM and 3D models; (iii) automated detection of illegal mining traces and anomalies; and (iv) environmental impact monitoring for 3E assessment. Literature evidence indicates these functions are individually feasible; validating the integrated model itself requires a dedicated Quang Ninh pilot, identified here as the next step.