標題: Titlebook: Disrupting Buildings; Digitalisation and t Theo Lynn,Pierangelo Rosati,Jennifer Kennedy Book‘‘‘‘‘‘‘‘ 2023 The Editor(s) (if applicable) and [打印本頁] 作者: affected 時間: 2025-3-21 20:09
書目名稱Disrupting Buildings影響因子(影響力)
書目名稱Disrupting Buildings影響因子(影響力)學科排名
書目名稱Disrupting Buildings網絡公開度
書目名稱Disrupting Buildings網絡公開度學科排名
書目名稱Disrupting Buildings被引頻次
書目名稱Disrupting Buildings被引頻次學科排名
書目名稱Disrupting Buildings年度引用
書目名稱Disrupting Buildings年度引用學科排名
書目名稱Disrupting Buildings讀者反饋
書目名稱Disrupting Buildings讀者反饋學科排名
作者: 謙虛的人 時間: 2025-3-21 21:16 作者: nonradioactive 時間: 2025-3-22 04:15
Book‘‘‘‘‘‘‘‘ 2023ming the deep renovation process, improving sustainability performance, and developing new services and markets..This open access book defines a deep renovation digital ecosystem for the 21st century, providing a state-of-the art review of current literature, suggesting avenues for new research, and作者: agnostic 時間: 2025-3-22 07:32
2662-1282 services and markets..This open access book defines a deep renovation digital ecosystem for the 21st century, providing a state-of-the art review of current literature, suggesting avenues for new research, and978-3-031-32309-6Series ISSN 2662-1282 Series E-ISSN 2662-1290 作者: 五行打油詩 時間: 2025-3-22 09:29
Theo Lynn,Pierangelo Rosati,Jennifer KennedyDefines and explores the key drivers and barriers for deep renovation.Offers insight from international experts that will be relevant to all major markets for construction.Digestible chapters provide 作者: 戰(zhàn)勝 時間: 2025-3-22 15:22 作者: 戰(zhàn)勝 時間: 2025-3-22 17:19
Overview of Development Finance Institutionsetal, 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作者: 正式通知 時間: 2025-3-22 23:19
https://doi.org/10.1007/978-3-031-38639-8, the artefacts and actors within it, and events that occur. Such monitoring is important for efficient construction management, dynamic peak demand reduction, affordability, and occupants’ well-being. Sensor networks based on Internet of Things (IoT) technologies represent an important prerequisite作者: 榨取 時間: 2025-3-23 01:23
Overview of Development Finance Institutions, cost management, and ultimately an information management framework that has the potential to enhance decision-making throughout the whole life-cycle of built assets. This chapter summarises state-of-the-art BIM and its benefits. It then considers the particular characteristics of deep renovation 作者: vanquish 時間: 2025-3-23 06:49 作者: PALL 時間: 2025-3-23 13:28
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 作者: 蕨類 時間: 2025-3-23 17:11 作者: 陪審團每個人 時間: 2025-3-23 18:43
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作者: anthesis 時間: 2025-3-24 02:01 作者: Adrenaline 時間: 2025-3-24 02:34 作者: STEER 時間: 2025-3-24 09:48 作者: 粘連 時間: 2025-3-24 13:29
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.作者: paleolithic 時間: 2025-3-24 16:11 作者: isotope 時間: 2025-3-24 21:19 作者: emission 時間: 2025-3-25 02:18
https://doi.org/10.1007/978-3-031-32309-6construction sector; digital technologies; sustainability engineering; architecture; mechanical engineer作者: 夜晚 時間: 2025-3-25 07:13
The Editor(s) (if applicable) and The Author(s) 2023作者: ferment 時間: 2025-3-25 11:15
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.作者: GNAW 時間: 2025-3-25 14:05 作者: 進取心 時間: 2025-3-25 19:05 作者: 形上升才刺激 時間: 2025-3-25 21:23
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.作者: 壟斷 時間: 2025-3-26 02:31
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.作者: 慷慨不好 時間: 2025-3-26 07:10
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.作者: FUSC 時間: 2025-3-26 12:08
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.作者: 揉雜 時間: 2025-3-26 14:23
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.作者: 神圣將軍 時間: 2025-3-26 18:01 作者: 驚呼 時間: 2025-3-26 21:43 作者: Flounder 時間: 2025-3-27 02:14
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.作者: overbearing 時間: 2025-3-27 07:02 作者: 失望未來 時間: 2025-3-27 10:01 作者: 鎮(zhèn)壓 時間: 2025-3-27 14:33
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.作者: MORPH 時間: 2025-3-27 18:19
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.作者: conjunctivitis 時間: 2025-3-28 00:40 作者: DEI 時間: 2025-3-28 04:13 作者: Prologue 時間: 2025-3-28 06:19 作者: extrovert 時間: 2025-3-28 10:34
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作者: 載貨清單 時間: 2025-3-28 18:02 作者: Blazon 時間: 2025-3-28 21:34 作者: 幻想 時間: 2025-3-29 02:52 作者: CHOKE 時間: 2025-3-29 06:20
Big Data and Analytics in the Deep Renovation Life Cycle,stry. 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 作者: Haphazard 時間: 2025-3-29 08:58 作者: exclamation 時間: 2025-3-29 12:07
Additive Manufacturing and the Construction Industry,se 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
