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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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11#
發(fā)表于 2025-3-23 13:28:42 | 只看該作者
Reitumetse Obakeng Mabokela,Yeukai A. Mlambostry. The availability of data is especially advantageous in the context of deep renovation, where it may significantly accelerate the decision-making process for building stock retrofit. This chapter covers Big Data and analytics in the context of deep renovation and shows how Machine Learning and
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發(fā)表于 2025-3-23 17:11:39 | 只看該作者
13#
發(fā)表于 2025-3-23 18:43:31 | 只看該作者
Self-Orienting Process and Schatzki’s Lensse complex and innovative geometries to build an object, building block, wall, or frame from a computer model. As such, it has potential opportunities for the construction industry and specific applications in the deep renovation process. While AM can provide significant benefits in the deep renovat
14#
發(fā)表于 2025-3-24 02:01:04 | 只看該作者
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發(fā)表于 2025-3-24 02:34:24 | 只看該作者
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發(fā)表于 2025-3-24 09:48:31 | 只看該作者
17#
發(fā)表于 2025-3-24 13:29:32 | 只看該作者
Financing Building Renovation: Financial Technology as an Alternative Channel to Mobilise Private Fy (FinTech) solutions such as crowdfunding and blockchain-based solutions such as tokenisation and smart contracts can provide to building owners and construction companies in terms of financing. Future avenues for research in this space are also presented.
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發(fā)表于 2025-3-24 16:11:34 | 只看該作者
19#
發(fā)表于 2025-3-24 21:19:42 | 只看該作者
20#
發(fā)表于 2025-3-25 02:18:23 | 只看該作者
https://doi.org/10.1007/978-3-031-32309-6construction sector; digital technologies; sustainability engineering; architecture; mechanical engineer
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