With the development of smart cities, the requirement of sampling spatial characteristics of building regarding to efficiencies and accuracies are becoming much higher.Focusing on those limitations of current available technologies in AEC market, which is poor of flexibilities, lack of intelligences, and high of labor cost, this paper has proposed a new solution based on UAV(Unmanned Aerial Vehicle)scanning and YOLO(You Only Look Once)recognition to enable the real-time identification and extraction of window components from as-built projects. In this paper, the algorithm of YOLOv3 is being optimized to train the algorithm model by using integrated dataset. Nginx is being used to build RTMP(Real Time Messaging Protocol)for receiving the data from UAV scanning through streaming server for displaying the live results in ground station. The proposed solution has improved the efficiencies of recognition and has reduced the delays of streaming, which reflects the advantages of UAV technologies from the aspects of simultaneous, efficiencies, and intelligences for satisfying those demands in building components detection.