Speaker
Description
21st century marked the era of widespread adoption of digital technologies in various sectors along with urban landscapes and building technologies. The advent of cutting-edge technological development intervened with the rapid evolution of urban landscapes and built environment. As a result, digitalization as a continuous and dynamic process has been seen as an antidote for the growing complex problems with the increasing rate of urbanization and subsequently emerging issues of efficient management and planning of a sustainable and healthy built environment. While the concepts of smart cities and smart buildings have emerged in order to systematically use information and communication technologies (ICT) to enhance efficiency, performance and to improve the overall quality of life, digital twin generated an arena to intertwine cyber and physical spaces. Differentiating from a sole digital model, digital twin is a virtual representation of a physical object, process or a system and its integration with the real-time data that provides the opportunity to simulate real-world scenarios. In principle, the available data derived form smart cities or buildings together with the digital technologies of artificial intelligence, data analytics and machine learning enable the development of a digital twin that can adapt and evolve in tandem with changes in the corresponding physical equivalents (Kaur et al., 2020). While mimicking the real-world counterparts’, digital twins facilitate data analysis, system monitoring and processes of planning and design through simulations and, pave the path to elaborate innovative solutions for contingency and complexity of today’s urban areas. Aligned with the objectives of smart city and smart building concepts, digital twins aim to enhance efficiency, performance, and quality of services (White et al., 2021). By leveraging technology, it seeks to improve overall quality of life for residents by addressing challenges such as energy consumption and thermal comfort, traffic congestion, waste management and space utilization. This study aims to investigate the potential of digital twins to provide a comprehensive and real-time understanding of smart cities and buildings, their role in decision-making processes and their contribution to create efficient, sustainable, and equitable management of urban environments.
References
Kaur, M. J., Mishra, V. P., & Maheshwari, P. (2020). The convergence of digital twin, IoT, and machine learning: transforming data into action. Digital twin technologies and smart cities, 3-17.
White, G., Zink, A., Codecá, L., & Clarke, S. (2021). A digital twin smart city for citizen feedback. Cities, 110, 103064.
| Keywords | Digital Twin; Smart City; Digitalization; Cyber-Physical Systems |
|---|---|
| Best Congress Paper Award | Yes |
