Establishing a cost-effective digital-twin model and analysis platform of urban built environments with AI and big data technology.
Digital twins are virtual replicas of physical objects that exist in the digital realm. Digital twins in the urban built environment have emerged as essential parts of smart cities and powerful tools for urban planning, design and management, and are actively promoted by governments. However, despite strong advocacy, the widespread adoption of digital-twin cities is still limited.
Therefore, we propose building a cost-effective digital-twin model and analysis platform for governments, design companies and practitioners, using AI and big data technology. Through our project, we aim to transform urban management and design practices with advanced tools and insights for informed decision-making and smart city development.
Mr Wei Di* (PhD student, Department of Architecture and Civil Engineering, City University of Hong Kong)
Mr Jiang Yuxiao (PhD student, Department of Architecture and Civil Engineering, City University of Hong Kong)
Ms Guan Xueqing (University College London)
Mr Chen Hongseng (University College London)
* Person-in-charge
(Info based on the team's application form)
- CityU HK Tech 300 Seed Fund (2023)