Entrance Design Using Human Movement Dynamics Through Spatial Tracking Data

Abstract

 This study investigates the enhancement of entrance design in architectural and urban contexts through the analysis of human movement dynamics derived from spatial tracking data. The research leverages technologies such as computer vision, pose estimation, and spatial analysis to understand pedestrian flows, interactions, and behaviors around entrances. The findings demonstrate that such insights allow for optimizing layouts to improve accessibility, reduce congestion, and preserve cultural or functional attributes. By synthesizing approaches from dynamic scene perception, trajectory prediction, shopper behavior analysis, crowd management, and spatial configurative methods, this study establishes evidence-based entrance design principles. The results contribute to the fields of architecture and urban planning by providing a comprehensive framework for integrating human movement data into the design process, ultimately leading to more efficient, safe, and user-centered entrance configurations