Digital Twin Computing for Urban Intelligence

Saeid Pourroostaei Ardakani (Hrsg.), Ali Cheshmehzangi (Hrsg.)

PDF
ca. 160,49

Springer Nature Singapore img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Geografie

Beschreibung

Digital Twin Computing for Urban Intelligence focuses on new and ongoing discourses in interdisciplinary research and practice in urban system and smart city development pathways. It approaches digital twin fundamentals and principals including theoretical foundations, conceptualisations, strategies and services/patterns to define and adapt digital twin solutions for urban applications - mainly sustainability.

This book highlights promising case studies and outlines digital twin design models and system architecture by examining key digital twin deployment practices such as data analysis, decision making, and service automation in the line with intelligent urban planning. It also emphasises on DT technologies such as cloud computing, AI, IoTs, and smart virtualisation and outlines the key benefits of the DT solutions in urban applications - mainly control and planning.

This book is intended for a wide range of audiences, including interested layperson audiences, undergraduate and graduate students in university, and researchers. The key benefits of this book are:

1- To introduce the theoretical principles and fundamentals of DT computing for urban intelligence.

2- To present the state-of-the-art DT technologies in urban planning and control.

3- To describe the practical deployment process of DT computing solutions for urban sustainability and intelligence.

Weitere Titel von diesem Autor
Weitere Titel in dieser Kategorie
Cover Inequality and Mobility
Katharina Grüneisl
Cover Climate Justice
Cass R. Sunstein
Cover The Atoms of Space
Balungi Francis
Cover Social-Ecological Consequences of Future Wildfires and Smoke in the West
Division of Behavioral and Social Sciences and Education

Kundenbewertungen

Schlagwörter

Urban Planning, Cloud Computing, Artificial Intelligence, Internet of Things, Urban Intelligence, Feedback Systems, Urban Sustainability, Digital Twins, Remote Sensing, Big Data Analysis