Beyond Data, Towards Sustainability: A Sydney Case Study on Urban Digital Twins
Ammar Sohail, Bojie Shen, Muhammad Aamir Cheema, Mohammed Eunus Ali,, Anwaar Ulhaq, Muhammad Ali Babar, Asama Qureshi

TL;DR
This paper explores Sydney’s urban digital twin, demonstrating its potential for sustainable urban planning through data integration, visualization, correlation analysis, and predictive modeling to support proactive decision-making.
Contribution
It provides a comprehensive case study of a city-scale digital twin, integrating diverse data sources and applying advanced analysis techniques for urban sustainability.
Findings
Digital twin enables spatial ranking of suburbs
Correlation analysis reveals variable interdependencies
Machine learning forecasts traffic crash risks
Abstract
As urban areas grapple with unprecedented challenges stemming from population growth and climate change, the emergence of urban digital twins offers a promising solution. This paper presents a case study focusing on Sydney's urban digital twin, a virtual replica integrating diverse real-time and historical data, including weather, crime, emissions, and traffic. Through advanced visualization and data analysis techniques, the study explores some applications of this digital twin in urban sustainability, such as spatial ranking of suburbs and automatic identification of correlations between variables. Additionally, the research delves into predictive modeling, employing machine learning to forecast traffic crash risks using environmental data, showcasing the potential for proactive interventions. The contributions of this work lie in the comprehensive exploration of a city-scale digital…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsSmart Cities and Technologies
