Adaptive Fractal Quadtree Approach for Efficient Drone-Based Construction Site Safety Inspection

This study presents a novel approach for optimizing the flight paths of multiple drones during construction site inspection and monitoring by leveraging image compression techniques, specifically the fractal quadtree method. Traditional path planning methods often fail to account for varying levels of complexity across the construction site, leading to inefficiencies in energy consumption and scanning time. By applying the fractal quadtree approach, we dynamically adapt grid sizes based on the complexity of the initial captured site images, allowing drones to prioritize more intricate areas while minimizing focus on simpler regions. Simulation results demonstrate that this method efficiently reduces the number of required scans compared to conventional approaches, significantly improving the overall efficiency of construction site inspections. The integration of this adaptive path planning strategy provides a scalable and time-saving solution for hazard identification and site monitoring, ensuring more efficient use of drone resources.