Integrating Digital Twins in Urban Sustainability: A Framework for University Campus Applications

In the contemporary urban environment, the convergence of smart technologies, virtual innovations, and the Internet of Things (IoT) has catalysed the need for robust frameworks that enhance data collection, visualisation, and analysis. Digital twins, scalable from individual buildings to entire cities, integrate diverse data sources to offer critical insights into facility management, asset lifecycle, and the optimisation of design and performance. While the application of digital twins has been explored extensively over the past two decades, there remains a significant gap in comprehensive frameworks that facilitate their development and implementation across various scales. This chapter introduces a systematic framework tailored for the creation of a digital twin for university campuses, which, with adaptations, can be extended to broader urban contexts such as towns and cities. This framework leverages underutilised data, employing advanced interpolation and visualisation techniques to generate analysis-ready datasets for simulations (e.g., flooding, energy consumption) and spatial mappings of functionality and occupancy. Such integrative approaches not only enhance campus planning and policymaking but also serve as a model for urban sustainability efforts. Further, this research delineates the specific methodologies for data extraction, transformation, and loading that are critical to optimising the digital twin framework at a campus level. The outcomes presented herein aim to guide future large-scale digital twin projects and provide urban and architectural researchers with a novel perspective on the potential of digital twins in future design, management, and sustainable planning. This includes predictive analytics for problem-solving, risk assessment, cost management, operation and maintenance, and performance enhancement in urban settings.