Analysis of Spatial Data Structures for Proximity Detection

作     者：Anupreet Walia Jochen Teizer 

作者机构：School of Civil and Environmental Engineering Georgia Institute of Technology 

出 版 物：《Tsinghua Science and Technology》 (清华大学学报（自然科学版（英文版）)

年 卷 期：2008年第13卷第S1期

页      面：102-107页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 080401[工学-精密仪器及机械] 0804[工学-仪器科学与技术] 080402[工学-测试计量技术及仪器] 0838[工学-公安技术] 

基　　金：the USA National Science Foundation (NSF) 

主　　题：proximity detection real-time resource tracking safety spatial data structures work zones 

摘      要：Construction is a dangerous business. According to statistics, in every of the past thirteen years more than 1000 workers died in the USA construction industry. In order to minimize the overall number of these incidents, the research presented in this paper investigates to monitor and analyze the trajectories of construction resources first in a simulated environment and later on the actual job site. Due to the complex nature of the construction environment, three dimensional (3D) positioning data of workers is hardly collected. Although technology is available that allows tracking construction assets in real-time, indoors and outdoors, in 3D, at the same time, the continuously changing spatial and temporal arrangement of job sites requires any successfully working data processing system to work in real-time. This research paper focuses is safety on spatial data structures that offer the capability of realigning itself and reporting the distance of the closest neighbor in real-time. This paper presents results to simulations that allow the processing of real-time location data for collision detection and proximity analysis. The presented data structures and perform-ance results to the developed algorithms demonstrate that real-time tracking and proximity detection of resources is feasible.