Digital twin (DT) offers significant opportunities for enhancing facility management (FM) in campus environments. However, existing research often focuses narrowly on isolated domains, such as point-cloud geometry or energy analytics, without providing a scalable and interoperable workflow that integrates building geometry, equipment metadata, and operational data into a unified FM platform. This study proposes a comprehensive framework for scalable digital-twin deployment in smart campus buildings by integrating 3D laser scanning, BIM modeling, and IoT-enabled data visualization to support facility operations and maintenance. The methodology includes: (1) reality capture using terrestrial laser scanning and structured point-cloud processing; (2) development of an enriched BIM model incorporating architectural, mechanical, electrical, plumbing, conveying, and sensor systems; and (3) creation of a digital-twin environment that links equipment metadata, maintenance policies, and simulated IoT data within a digital-twin management platform. A case study of the Price Gilbert Building at Georgia Tech demonstrates the implementation of this workflow. A total of 509 equipment items were modeled and embedded with OmniClass classifications into the digital twin. Ten interactive dashboards were developed to visualize system performance. Results show that the proposed framework enables centralized asset documentation, improved system visibility, and enhanced preventive and reactive maintenance workflows. Although most IoT data were simulated due to limited existing sensor infrastructure, the prototype validates the feasibility of a scalable digital twin for facility management and establishes a reference model for real-time monitoring, analytics integration, and future autonomous building operations.

翻译：数字孪生（DT）为校园环境中的设施管理（FM）提供了重要机遇。然而，现有研究往往局限于孤立领域，如点云几何或能源分析，未能提供一种将建筑几何、设备元数据和运营数据整合到统一FM平台的可扩展、可互操作的工作流。本研究提出了一种面向智慧校园建筑的可扩展数字孪生部署综合框架，通过集成三维激光扫描、BIM建模和物联网驱动的数据可视化，以支持设施运营与维护。该方法包括：（1）利用地面激光扫描与结构化点云处理实现实景捕捉；（2）开发包含建筑、机械、电气、给排水、输送及传感器系统的增强型BIM模型；（3）在数字孪生管理平台内创建连接设备元数据、维护策略与模拟物联网数据的数字孪生环境。以佐治亚理工学院Price Gilbert大楼为例展示了该工作流的实施过程。共计509项设备被建模并嵌入OmniClass分类至数字孪生中，开发了十个交互式仪表板以可视化系统性能。结果表明，所提框架实现了集中化资产文档管理、提升的系统可见性以及优化的预防性与响应性维护工作流。尽管因现有传感器基础设施有限，大部分物联网数据为模拟数据，但原型验证了可扩展数字孪生用于设施管理的可行性，并为实时监测、分析集成及未来自主化建筑运营建立了参考模型。