Mentor Based AI-Driven Arctic Architecture: Designing Climate-Responsive Facades and Urban Systems

About This Course

This 3-week course dives deep into the integration of artificial intelligence (AI) in Arctic architecture—focusing on designing climate-responsive facades, bespoke architectural elements, and resilient urban infrastructures. Participants will gain hands-on experience with AI tools to develop sustainable solutions tailored to the unique challenges of Arctic and sub-Arctic urban environments. The course combines environmental simulation, data-driven design, and AI-powered tools to create adaptive, energy-efficient, and resilient systems for extreme climates.

Aim

To empower participants to harness AI for developing adaptive facades and urban systems designed specifically for the cold, dynamic conditions of Arctic climates. The course focuses on climate-responsive design, sustainability, and urban resilience through advanced technology.

Course Objectives

• Foster innovation in designing cold-climate responsive architecture

• Demonstrate real-world AI applications in sustainable architecture

• Equip professionals with simulation and optimization tools for Arctic design

• Promote interdisciplinary thinking across design, data science, and climate adaptation

• Support resilient, culturally sensitive urban development in extreme environments

• Enable the design of AI-driven adaptive facades and smart infrastructure in Arctic cities

Course Structure

Module 1 — AI-Enhanced Climate-Responsive Facades

• Introduction to AI in Architecture: What is climate-adaptive facade design, and how can AI drive it?

• Key Concepts: Dynamic building envelopes, AI in real-time environmental data integration, and smart adaptive systems for Arctic climates

• Applications in Arctic Environments: Designing facades that adapt to extreme weather conditions (wind, cold, light variation)

• Tool: Facade Master – AI-powered tool for designing and analyzing responsive facades

• Activity: Participants will design a climate-responsive facade prototype for a hypothetical Arctic building, optimizing for energy efficiency and thermal comfort

• Objective: Learn to develop AI-driven facades that respond to environmental stimuli in Arctic climates

Module 2 — Designing Bespoke Architectural Elements with AI

• Bespoke Architecture and Modular Design with AI: Using AI to generate customizable and modular architectural elements suited for extreme cold climates

• Key Concepts: Material optimization, structural integrity, and energy-efficient designs

• Role of AI: How AI can enhance modular design, adapt structures to Arctic conditions, and improve energy performance

• Tool: Exterior AI – A tool for creating bespoke architectural elements with AI

• Activity: Upload sketches or photos of architectural elements and use Exterior AI to create bespoke designs for Arctic environments

• Objective: Develop modular architectural fragments tailored to Arctic conditions, ensuring functionality, sustainability, and adaptability

Module 3 — AI in Arctic Urban Planning and Infrastructure

• Urbanism in the Arctic: Understanding the unique challenges and opportunities of urban planning in extreme cold climates

• Key Concepts: AI-assisted infrastructure systems for energy, heating, cooling, and water management

• Integrating AI with IoT: How predictive maintenance and real-time management can optimize urban systems in Arctic cities

• Tool: Urban Visions – AI-powered tool for designing and simulating urban infrastructure systems

• Activity: Participants will design and simulate smart urban infrastructure for an Arctic city, focusing on heating networks, energy management, and transportation systems

• Objective: Develop a comprehensive AI-powered urban infrastructure plan for a sustainable and climate-responsive Arctic city

Who Should Enrol?

• Architects and computational designers interested in climate-responsive architecture

• Urban planners and smart city professionals working on sustainable infrastructure in extreme climates

• Environmental and civil engineers focused on developing resilient systems for cold climates

• AI/ML practitioners working in climate design and built environments

• Postgraduate students and researchers in architecture, urban planning, or climate science