Titlebook: Disrupting Buildings; Digitalisation and t Theo Lynn,Pierangelo Rosati,Jennifer Kennedy Book‘‘‘‘‘‘‘‘ 2023 The Editor(s) (if applicable) and

惊呼

Flounder

Building Information Modelling,al Intelligence (AI) and Machine Learning (ML) to BIM models to optimise deep renovation project delivery. The prospects for this are encouraging, but further development work, including the creation of ontologies that are appropriate for renovation work, is still needed.

overbearing

失望未来

镇压

Additive Manufacturing and the Construction Industry,nstruction industry are outlined. This chapter also explores the benefits and challenges of implementing AM within the construction industry before concluding with a discussion of the future areas of development for AM in construction.

MORPH

Cybersecurity Considerations for Deep Renovation,rity frameworks, standards, guidelines and codes of practice. The chapter also discusses the need for a contingency approach in deep renovation cybersecurity due to the varying requirements of each project and organisation.

conjunctivitis

DEI

Prologue

extrovert

Deep Renovation: Definitions, Drivers and Barriers,etal, economic, environmental, energy security, quality, opportunistic, and catalytic motivations and benefits. At the same time, both deep renovation and digital technology adoption to support deep renovation are impacted by challenges presented in humans, organisational processes, technologies and