AI for Smart Building Design & Energy-Efficient Systems
Transforming Building Design: AI for Energy Efficiency and Carbon Footprint Reduction
About This Course
This workshop explores how Artificial Intelligence can revolutionize smart building design by optimizing energy use, automating systems, and reducing environmental impact. Participants will gain hands-on experience in developing AI-driven energy management systems, forecasting energy consumption, and integrating renewable energy solutions. Designed for professionals in architecture, construction, and energy management, the workshop provides practical tools for creating sustainable, energy-efficient buildings.
Aim
This workshop aims to explore AI’s role in designing smart, energy-efficient buildings by optimizing energy use, automating systems, and reducing environmental impact. Participants will gain hands-on experience in applying AI for energy management and integrating renewable energy solutions in building design.
Workshop Objectives
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Explore AI applications in designing energy-efficient smart buildings and optimizing building systems.
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Develop AI models for energy consumption forecasting and optimization in buildings.
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Learn to apply AI for reducing environmental impact and enhancing sustainability in building designs.
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Gain practical skills in integrating renewable energy systems into smart buildings using AI.
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Implement AI-driven energy management systems and automation solutions for smart buildings.
Workshop Structure
📅 Day 1 – AI for Smart Building Design
- Introduction to AI applications in designing energy-efficient and sustainable buildings.
- Hands-on: Developing smart building designs using AI to optimize energy consumption (Google Colab).
- Energy Management Systems for Smart Buildings: AI-driven optimization of HVAC and lighting systems.
- Hands-on: Building AI-based energy management systems for smart buildings (Jupyter Notebook).
👉 Outcome: AI-driven smart building and energy management models + .ipynb.
📅 Day 2 – AI for Energy Consumption Forecasting & Environmental Impact Reduction
- Using machine learning models to predict and optimize energy consumption in buildings.
- Hands-on: Building energy consumption forecasting models (Google Colab).
- AI-based techniques to reduce the carbon footprint and environmental impact of buildings.
- Hands-on: Building AI models for environmental impact reduction in smart buildings (Jupyter Notebook).
👉 Outcome: Energy consumption and environmental impact reduction models + .ipynb.
📅 Day 3 – AI in Building Automation & Renewable Energy Integration
- Exploring how AI can automate and optimize building functions for energy efficiency and comfort.
- Hands-on: Implementing AI in Building Automation Systems (BAS) for energy optimization (Google Colab).
- Integrating renewable energy systems in smart buildings: AI for managing solar, wind, and other energy sources.
- Hands-on: Developing AI-driven renewable energy integration models for buildings (Jupyter Notebook).
👉 Outcome: AI-driven building automation and renewable energy integration models + .ipynb.
Who Should Enrol?
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Architects, urban planners, and construction professionals focused on smart building design and energy efficiency.
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Engineers and energy management experts aiming to optimize energy use and reduce environmental impact.
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Researchers, academics, and students in architecture, civil engineering, AI, and energy management.
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Professionals looking to integrate AI into building automation and energy management systems.
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Basic knowledge of AI concepts is recommended.
Important Dates
Registration Ends
December 17, 2025
IST 4:30 PM
Workshop Dates
December 17, 2025 – December 19, 2025
IST 5:30 PM
Workshop Outcomes
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Develop AI models for designing energy-efficient smart buildings and optimizing building systems.
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Gain hands-on experience in creating AI-driven energy management systems.
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Learn to forecast and optimize energy consumption patterns using machine learning.
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Apply AI to reduce environmental impact and improve building sustainability.
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Build AI models for integrating renewable energy systems into smart buildings.
Fee Structure
Student
₹1999 | $65
Ph.D. Scholar / Researcher
₹2999 | $75
Academician / Faculty
₹3998 | $85
Industry Professional
₹5999 | $106
What You’ll Gain
- Live & recorded sessions
- e-Certificate upon completion
- Post-workshop query support
- Hands-on learning experience
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