Showcasing a digital twin for higher educational buildings: developing the concept toward human centricity

Katarina Bäcklund, Per Lundqvist, Marco Molinari
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Abstract

Digital twin technology is an emerging technology within the built environment. Yet, there are many unexplored opportunities to utilize digital twins for facilitating the transformation toward a climate-neutral building stock while also meeting the expectations from the building occupants. This article presents a case study of a digital twin, developed for an existing commercial building stock of campus areas in Sweden. The overarching purpose of the digital twin is to support both building occupants and building operators. This two-fold human-centric approach represents a novel approach for building digital twins. The digital twin is based on 3D scanning, and together with geospatial data, a real-like navigational indoor environment is created. Three innovative features are presented: the building analysis module, the digital twin mobile application, and the building operations module. The results show that the digital twin improves the building occupant’s experience by supporting navigation and providing access to the room booking system via this dedicated interface. Building management is also benefited by the digital twin through easier access to building data aggregated into one platform and a state-of-the-art analysis tool for optimizing the use of indoor space. The digital twin holds future potential to achieve operational excellence by incorporating feedback mechanisms and utilizing artificial intelligence to enable intelligent fault detection and prevention.
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展示高等教育建筑的数字孪生:发展以人为本的概念
数字孪生技术是建筑环境领域的一项新兴技术。然而,利用数字孪生技术促进向气候中和建筑群的转变,同时满足建筑使用者的期望,还有许多尚未开发的机会。本文介绍了一个数字孪生的案例研究,该案例是针对瑞典校园区域的现有商业建筑群开发的。数字孪生的首要目的是为建筑使用者和建筑运营商提供支持。这种以人为本的双重方法是构建数字孪生的一种新方法。数字孪生以三维扫描为基础,结合地理空间数据,创建了一个类似真实导航的室内环境。报告介绍了三个创新功能:建筑分析模块、数字孪生移动应用和建筑运营模块。研究结果表明,数字孪生支持导航,并可通过专用界面访问房间预订系统,从而改善了楼宇使用者的体验。数字孪生系统还能更方便地访问汇集到一个平台的楼宇数据,并通过最先进的分析工具优化室内空间的使用,从而使楼宇管理受益匪浅。未来,数字孪生系统还将融入反馈机制,利用人工智能实现智能故障检测和预防,从而实现卓越运营。
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