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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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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
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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
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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
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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
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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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