Data-driven BIM for energy efficient building design
Classics of the data-driven BIM for energy efficient design -- Sustainability, information and optimisation: antecedents of the data and BIM-enabled EED -- BIM and energy efficient design -- Building energy parameters -- AI algorithms development -- BIM-inherited EED framework development and verifi...
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| Weitere Verfasser: | , |
| Format: | UnknownFormat |
| Sprache: | eng |
| Veröffentlicht: |
London, New York
Routledge
2023
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| Schriftenreihe: | Spon Research
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| Schlagworte: | |
| Online Zugang: | Inhaltsverzeichnis |
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Tag hinzufügen | Zusammenfassung: | Classics of the data-driven BIM for energy efficient design -- Sustainability, information and optimisation: antecedents of the data and BIM-enabled EED -- BIM and energy efficient design -- Building energy parameters -- AI algorithms development -- BIM-inherited EED framework development and verification. "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 develop its functional solutions with a focus towards four crucial aspects of building envelop, building layout, occupant behaviour and heating, ventilation and air-conditioning (HVAC) systems. Drawn from the 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 which is missed in the extant literature and this book aims to fill that. This approach will inform a vision for future, 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 are 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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| Beschreibung: | Literaturangaben |
| Beschreibung: | xvi, 170 Seiten Illustrationen, Diagramme |
| ISBN: | 9781032073484 978-1-032-07348-4 9781032075549 978-1-032-07554-9 |