Mentor Based AI & Biodesign for Sustainable Cities: Smart Buildings, Green Architecture & Urban Systems

About This Course

This four-week, hands-on course teaches you how to combine biodesign—including biomimicry, living façades, green roofs, vertical greenery, and bio-based materials—with AI-driven building and city analytics to enhance comfort, reduce energy use, and cut carbon emissions.

Step by step, you’ll move from building-scale fundamentals—covering comfort, daylight, shading, and energy—to AI-based forecasting and optimization. You will then expand to district- and city-level decision-making. The course concludes with a capstone project where you model and compare “business-as-usual” vs “AI + biodesign–optimized” futures, linking building → district → city through a structured scenario workflow in Google Colab.

Aim

This course is designed to equip participants with the skills to apply biodesign principles and AI-driven performance modeling for designing and optimizing climate-responsive buildings and sustainable urban systems—scaling from individual buildings to entire districts and cities.

Course Objectives

By the end of this course, participants will be able to:

• Understand biodesign strategies for climate-responsive, sustainable architecture
• Define and measure comfort, daylight, shading, energy, and emissions goals
• Work with building and urban datasets (occupancy, weather, indoor environmental quality indicators)
• Build basic AI/ML models for energy forecasting and performance analysis in Google Colab
• Explore smart building controls and AI-driven optimization with PV/BIPV integration
• Deliver a capstone linking building → district → city scenarios for actionable decision-making

Course Structure

Module 1: Biodesign and Climate-Responsive Architecture

• Biodesign essentials: biomimicry, green architecture, living façades, green roofs, vertical greenery
• Climate-adaptive and bio-based materials for façades and building envelopes
• Performance framing: thermal comfort, daylight, shading, and energy-use fundamentals
• Hands-on: Map biodesign strategies to measurable performance objectives

Module 2: Data and AI Foundations for Building Performance

• Building energy & environment datasets: loads, occupancy, schedules, weather, and IEQ indicators
• AI/ML for energy forecasting: time-series and ML models for predicting energy consumption
• Linking design form and materials to energy performance and model features
• Hands-on: Colab notebook for energy-consumption prediction using sample building data

Module 3: Smart Buildings, Automation, and Renewables

• Smart building systems & controls: HVAC, lighting, sensors, BMS/BAS; balancing comfort and efficiency
• AI-driven control and optimization: setpoints, schedules, operational strategies
• Rooftop PV & BIPV integration: demand, renewables, storage, peak shaving, and emissions reduction
• Hands-on: Colab notebook to optimize a simple HVAC + lighting + rooftop PV scenario

Module 4: AI for Smart Urban Systems and Capstone

• Smart cities with AI: land-use, density, green/blue networks, and resource flows
• City-scale indicators: aggregating building data to district level; mobility, EV charging, sustainability metrics
• Governance and policy: decision-support dashboards and scenario planning
• Hands-on Capstone: Multi-scale scenario model (building → district → city) in Colab, comparing business-as-usual vs AI + biodesign–optimized futures

Who Should Enrol?

This course is ideal for:

• Architecture, urban planning, and design students/professionals
• Civil, environmental, energy, and sustainability engineers
• Building performance and green building practitioners (HVAC, energy modelling, IEQ)
• Smart city, GIS, and urban systems professionals
• Data science/AI/ML learners interested in climate, buildings, and urban analytics
• Policy, governance, and sustainability stakeholders working on resilient city solutions