Development of next-generation methodologies of resource scheduling, augmented reality visualization, and resource tracking for construction project management

在可预见的未来，4D建模(3D CAD Plus Time)和建筑信息建模(BIM)技术将成为建筑业的主流。然而，它们在建筑工程中的应用效果在很大程度上取决于开发具有成本效益的、动态数据驱动的方法来调度、跟踪和可视化建筑资源。为了满足建设项目计划和控制中的应用需求，本研究旨在开发新一代方法，用于现场关键施工资源的调度、跟踪、定位和实时三维建模，这些资源包括重型设备、材料、工人和工具。本研究是在PI以往研究成果的基础上提出的：(1)提出施工调度的关键路径法；(2)应用机器人全站仪对隧道掘进机在微隧道掘进和顶管施工过程中进行跟踪定位；(3)利用数码相机和摄影测量实现地下基础设施建设的增强现实(AR)可视化。这项研究将把各种实时计算分析与测量自动化和数据通信的先进技术结合起来。预计(1)由此产生的资源调度分析将解决已建立的项目调度方法中固有的基本限制；(2)可以密切监控调度分析得出的资源分配计划的实施情况，并根据现场的实际情况动态调整；(3)资源部署和利用的状态可以在AR可视化中实时绘制-这也有助于提高现场的效率、安全性和作业成本计算。有了这笔赠款，PI将利用现有的优势，为在亚利桑那大学建立一个基础更广泛的建筑研究项目做出贡献。从长远来看，这项研究将为未来建设工程和项目管理的工程分析集成、动态数据驱动平台的开发和部署奠定坚实的基础。

4D modeling (3D CAD plus time) and building information modeling (BIM) technologies will turn mainstream in the construction industry in the foreseeable future. Yet, their application effectiveness in construction engineering largely hinges on development of cost-effective, dynamic-data-driven methodologies for scheduling, tracking, and visualizing construction resources. In order to cater for application needs in planning and control of construction projects, the present research is intended to develop next-generation methodologies for scheduling, tracking, positioning, real-time 3D modeling of critical construction resources on site, including heavy equipment, materials, laborers and tools. This research is proposed based on the PI's previous research achievements in (1) advancing critical path method for construction scheduling; (2) applying robotic total station to track and position tunnel boring machine during microtunneling and pipe-jacking; and (3) utilizing digital camera and photogrammetry to realize augmented reality (AR) visualization for subsurface infrastructure construction. The research will combine various real-time computing analyses with advanced technologies for surveying automation and data communications. It is anticipated (1) the resulting resource scheduling analysis will address fundamental limitations inherent in established project scheduling methodologies; (2) implementation of the resource allocation plan derived from scheduling analysis can be closely monitored and dynamically adjusted to actual site situations; and (3) the state of resource deployment and utilization can be mapped in AR visualization in real time- which is also instrumental in improving efficiency, safety, and job costing onsite. With this grant, the PI will leverage existing strengths and contribute to establishing a more broadly based construction research program at the U of A. In the long run, this research will lay a solid foundation for future development and deployment of an engineering-analysis-integrated, dynamic-data-driven platform for construction engineering and project management.