Developing a Digital Twin at Building and City Levels: Case Study of West Cambridge Campus

TLDR

A digital twin is a digital replica of physical assets that uses AI and data analytics to learn and predict conditions, but its application to buildings and infrastructure, especially during the long operation and maintenance phase, remains in early stages. The paper aims to develop and validate a systematic, multitier architecture for digital twins at building and city levels, providing a clear roadmap and lessons for effective operation and maintenance. The authors present a multitier architecture that integrates heterogeneous data sources, supports data querying and analysis, and facilitates decision‑making in O&M, thereby bridging human interactions with buildings and cities. The demonstrator at West Cambridge successfully integrated heterogeneous data, enabled O&M decision‑making, and produced a clear roadmap for practitioners, policymakers, and researchers to advance digital twin implementation at building and city levels.

Abstract

A digital twin (DT) refers to a digital replica of physical assets, processes, and systems. DTs integrate artificial intelligence, machine learning, and data analytics to create living digital simulation models that are able to learn and update from multiple sources as well as represent and predict the current and future conditions of physical counterparts. However, current activities related to DTs are still at an early stage with respect to buildings and other infrastructure assets from an architectural and engineering/construction point of view. Less attention has been paid to the operation and maintenance (O&M) phase, which is the longest time span in the asset life cycle. A systematic and clear architecture verified with practical use cases for constructing a DT would be the foremost step for effective operation and maintenance of buildings and cities. According to current research about multitier architectures, this paper presents a system architecture for DTs that is specifically designed at both the building and city levels. Based on this architecture, a DT demonstrator of the West Cambridge site of the University of Cambridge in the UK was developed that integrates heterogeneous data sources, supports effective data querying and analysis, supports decision-making processes in O&M management, and further bridges the gap between human relationships with buildings/cities. This paper aims at going through the whole process of developing DTs in building and city levels from the technical perspective and sharing lessons learned and challenges involved in developing DTs in real practices. Through developing this DT demonstrator, the results provide a clear roadmap and present particular DT research efforts for asset management practitioners, policymakers, and researchers to promote the implementation and development of DT at the building and city levels.