Data-driven BIM for energy efficient building design

by Banihashemi, Saeed

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Title Statements

Full title :Data-driven BIM for energy efficient building design / Saeed Banihashem, Hamed Golizadeh and Farzad Pour Rahimian.

Summary

"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"--

Edition Statements

Publication Date:©2023

Publication Statements

Publisher(s):Routledge Taylor & Francis Group
Place of Publication:Abingdon, Oxon
Language:eng
Publication Date:©2023

The Physical Object

Description:xvi, 170 pages : : illustrations ; : 25 cm.

Edition Identifiers

ISBN:9781032073484, 1032073489, 9781032075549, 1032075546
oclc:on1347373909
LC Classification:TH880
Dewey Decimal:720/.47

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.