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

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21#
發(fā)表于 2025-3-25 07:13:27 | 只看該作者
The Editor(s) (if applicable) and The Author(s) 2023
22#
發(fā)表于 2025-3-25 11:15:23 | 只看該作者
Deep Renovation: Definitions, Drivers and Barriers, and digital technology adoption to support deep renovation are impacted by challenges presented in humans, organisational processes, technologies and external environments. This chapter explores the key drivers and barriers to deep renovation and associated digitalisation. It establishes the motivation for the remainder of the book.
23#
發(fā)表于 2025-3-25 14:05:28 | 只看該作者
24#
發(fā)表于 2025-3-25 19:05:14 | 只看該作者
25#
發(fā)表于 2025-3-25 21:23:39 | 只看該作者
Embedded Sensors, Ubiquitous Connectivity and Tracking,antages and benefits of these technologies at the pre, during and post-renovation stages are discussed together with different use cases. The value of sensor network infrastructures and the legal and ethical implications of the use of such sensor infrastructures is also discussed.
26#
發(fā)表于 2025-3-26 02:31:45 | 只看該作者
Intelligent Construction Equipment and Robotics,helps in their benefits by defining relevant metrics while considering their pitfalls in terms of quality, safety, time, and cost. This framework assists practitioners in decision-making for adopting IER in their construction operation.
27#
發(fā)表于 2025-3-26 07:10:32 | 只看該作者
Overview of Development Finance Institutionsal 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.
28#
發(fā)表于 2025-3-26 12:08:46 | 只看該作者
Reitumetse Obakeng Mabokela,Yeukai A. Mlambop renovation and discusses a series of use cases, applications, advantages, and benefits as well as challenges and barriers. Finally, Big Data and deep renovation prospects are discussed, including future potential developments and guidelines.
29#
發(fā)表于 2025-3-26 14:23:46 | 只看該作者
Terhi Nokkala,Bojana ?ulum,Tatiana Fumasoli the state-of-the-art deep learning methods for digital twins and discusses some real-life use cases. Finally, the chapter discusses the benefits and challenges associated with the adoption of digital twins.
30#
發(fā)表于 2025-3-26 18:01:48 | 只看該作者
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