Data-driven BIM for Energy Efficient Building Design
eBook - ePub

Data-driven BIM for Energy Efficient Building Design

  1. 216 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Data-driven BIM for Energy Efficient Building Design

About this book

This research book aims to conceptualise the scale and spectrum of Building Information Modelling (BIM) and Artificial Intelligence (AI) approaches in energy efficient building design and to develop its functional solutions with a focus on four crucial aspects of building envelop, building layout, occupant behaviour and heating, ventilation and air-conditioning (HVAC) systems. Drawn from theoretical development on the sustainability, informatics and optimisation paradigms in built environment, the energy efficient building design will be marked through the power of data and BIM-intelligent agents during the design phase. It will be further developed via smart derivatives to reach a harmony in the systematic integration of energy efficient building design solutions, a gap that is missed in the extant literature and that this book aims to fill. This approach will inform a vision for future and provide a framework to shape and respond to our built environment and how it transforms the way we design and build. By considering the balance of BIM, AI and energy efficient outcomes, the future development of buildings will be regenerated in a direction that is sustainable in the long run. This book is essential reading for those in the AEC industry as well as computer scientists.

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Yes, you can access Data-driven BIM for Energy Efficient Building Design by Saeed Banihashemi,Hamed Golizadeh,Farzad Pour Rahimian in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Architecture Design. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half Title
  3. Series
  4. Title
  5. Copyright
  6. Dedication
  7. Contents
  8. List of Figures
  9. List of Tables
  10. List of Abbreviations
  11. Preface
  12. 1 Classics of Data-Driven BIM for Energy Efficient Design
  13. 2 Sustainability, Information and Optimisation: Antecedents of the Data and BIM-Enabled EED
  14. 3 BIM and Energy Efficient Design
  15. 4 Building Energy Parameters
  16. 5 AI Algorithms Development
  17. 6 BIM-Inherited EED Framework Development and Verification
  18. 7 Conclusion
  19. Index