Intelligent inspection of building exterior walls using UAV and mixed reality based on man-machine-environment system engineering

With increased durability, the safety hazards of building exterior walls have increased significantly. Traditional inspection methods for exterior walls primarily rely on manual labor, which is high-risk and inefficient. Although Unmanned Aerial Vehicle (UAV) have been utilized for exterior wall inspections, their potential to fully leverage human expertise and data processing capabilities remains underexplored. Therefore, based on Man-Machine-Environment System Engineering (MMESE) theory, this paper proposed an inspection method that integrates UAV and Mixed Reality (MR) to improve inspection efficiency and personnel involvement through data collection, analysis and management. The method includes the construction of an MR-based digital inspection environment, followed by the implementation of semi-automatic control and data acquisition of UAV in the constructed digital environment, and the visual management and mapping of defect data. The experimental results show that the proposed method can effectively complete the collection, analysis, and management of exterior wall defect data. It provides technical support for the intelligent inspection of building exterior walls and a theoretical foundation for advancing the MMESE.