Urban digital twins

URB-410 / 4 crédits

Enseignant: Kaplan Frédéric

Langue: Anglais

Summary

This course explores urban digital twins through theory and hands-on modeling. Students build dynamic models integrating real-time, historical, and predictive data. A project on the EPFL campus using real data serves as the case study.

Content

This course offers an introduction to urban digital twins, focusing on their theoretical foundations, practical implementation, and role as decision-support systems, with a specific emphasis on the EPFL campus. As cities and large institutional sites become increasingly complex, the need for sophisticated simulation and AI-based modeling technologies is more critical than ever. Urban digital twins serve as integrative platforms that combine spatial models, real-time data, historical context, and predictive modeling to support urban planning, infrastructure management, mobility analysis, energy optimization, and environmental stewardship.

Throughout the course, students engage with the principles of creating digital replicas of urban environments that are dynamic, interactive, and capable of simulating real-world conditions. Topics include recent advances in data acquisition techniques, data management strategies, AI-based modeling, predictive analysis, and human-centered interfaces for exploring and querying urban systems.

The centerpiece of the course is a group project in which students progressively contribute to the development of a digital twin of the EPFL campus. This project is supported by case studies based on real data, covering domains such as energy, food, mobility, and campus services. It builds upon the work of students from previous years and contributes to a cumulative experimental platform for understanding, simulating, and improving the EPFL campus environment.

Keywords

urban digital twins, real-time data, predictive modeling, AI-based simulation, geospatial analysis, infrastructure systems, scenario planning, data governance.

 

Learning Prerequisites

Required courses

While prior knowledge of information technology, GIS, 3D modeling and AI is beneficial, it is not mandatory. The course is designed to accommodate students from various technical backgrounds, providing foundational training as needed.

Learning Outcomes

By the end of the course, the student must be able to:

  • Explain the foundational concepts of urban digital twins and understand their role in contemporary urbanism
  • Manage the planning and execution of a urban digital twin model, incorporating historical data and future projections
  • Analyze the challenges and opportunities associated with implementing digital twins in urban settings.

Transversal skills

  • Plan and carry out activities in a way which makes optimal use of available time and other resources.
  • Make an oral presentation.
  • Respect the rules of the institution in which you are working.
  • Use a work methodology appropriate to the task.
  • Communicate effectively with professionals from other disciplines.
  • Negotiate effectively within the group.
  • Set objectives and design an action plan to reach those objectives.
  • Assess progress against the plan, and adapt the plan as appropriate.

Teaching methods

Lectures, invited lectures and group project

Expected student activities

Active participation and group project. Given the interactive and collective nature of the course, the presence of all the registered student is mandatory.

Assessment methods

(Group) Case study presentation

(Group) Midterm presentation

(Group) Final presentation

(Individual) Short Exam during the semester concerning the key concepts of the course

Resources

Notes/Handbook

A 200+ pages textbook is available

Moodle Link

Dans les plans d'études

  • Semestre: Printemps
  • Forme de l'examen: Pendant le semestre (session d'été)
  • Matière examinée: Urban digital twins
  • Cours: 3 Heure(s) hebdo x 14 semaines
  • Projet: 1 Heure(s) hebdo x 14 semaines
  • Type: optionnel
  • Semestre: Printemps
  • Forme de l'examen: Pendant le semestre (session d'été)
  • Matière examinée: Urban digital twins
  • Cours: 3 Heure(s) hebdo x 14 semaines
  • Projet: 1 Heure(s) hebdo x 14 semaines
  • Type: optionnel
  • Semestre: Printemps
  • Forme de l'examen: Pendant le semestre (session d'été)
  • Matière examinée: Urban digital twins
  • Cours: 3 Heure(s) hebdo x 14 semaines
  • Projet: 1 Heure(s) hebdo x 14 semaines
  • Type: optionnel
  • Semestre: Printemps
  • Forme de l'examen: Pendant le semestre (session d'été)
  • Matière examinée: Urban digital twins
  • Cours: 3 Heure(s) hebdo x 14 semaines
  • Projet: 1 Heure(s) hebdo x 14 semaines
  • Type: optionnel
  • Semestre: Printemps
  • Forme de l'examen: Pendant le semestre (session d'été)
  • Matière examinée: Urban digital twins
  • Cours: 3 Heure(s) hebdo x 14 semaines
  • Projet: 1 Heure(s) hebdo x 14 semaines
  • Type: optionnel
  • Semestre: Printemps
  • Forme de l'examen: Pendant le semestre (session d'été)
  • Matière examinée: Urban digital twins
  • Cours: 3 Heure(s) hebdo x 14 semaines
  • Projet: 1 Heure(s) hebdo x 14 semaines
  • Type: optionnel
  • Semestre: Printemps
  • Forme de l'examen: Pendant le semestre (session d'été)
  • Matière examinée: Urban digital twins
  • Cours: 3 Heure(s) hebdo x 14 semaines
  • Projet: 1 Heure(s) hebdo x 14 semaines
  • Type: optionnel
  • Semestre: Printemps
  • Forme de l'examen: Pendant le semestre (session d'été)
  • Matière examinée: Urban digital twins
  • Cours: 3 Heure(s) hebdo x 14 semaines
  • Projet: 1 Heure(s) hebdo x 14 semaines
  • Type: optionnel
  • Semestre: Printemps
  • Forme de l'examen: Pendant le semestre (session d'été)
  • Matière examinée: Urban digital twins
  • Cours: 3 Heure(s) hebdo x 14 semaines
  • Projet: 1 Heure(s) hebdo x 14 semaines
  • Type: optionnel

Semaine de référence

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