Description
Book SynopsisThe world’s extant building stock accounts for a significant portion of worldwide energy consumption and greenhouse gas emissions. In 2020, buildings and construction accounted for 36% of global final energy consumption and 37% of energy related CO2 emissions. The EU estimates that up to 75% of the EU’s existing building stock has poor energy performance, 85–95% of which will still be in use in 2050.
To meet the goals of the Paris Agreement on Climate Change will require a transformation of construction processes and deep renovation of the extant building stock. It is widely recognized that ICTs can play an important role in construction, renovation and maintenance as well as supporting the financing of deep renovation. Technologies such as sensors, big data analytics and machine learning, BIM, digital twinning, simulation, robots, cobots and UAVs, and additive manufacturing are transforming 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 offering perspectives from business, technology and industry domains.
This is an open access book.
Table of ContentsChapter 1 – Deep Renovation:Definitions, Drivers and Barriers
Chapter 1 defines the key elements of the deep renovationlifecycle. Investment in deep renovation is driven by a widerange of rationales including societal, economic,environmental, energy security, quality, opportunistic, andcatalytic motivations and benefits. At the same time, bothdeep renovation and digital technology adoption tosupport deep renovation are impacted by human,organisational, technological, and external environmentchallenges. This chapter explores the key drivers andbarriers for deep renovation and associated digitalisation.It establishes the motivation for the remainder of the book.
Chapter 2 - Embedded Sensors,Ubiquitous Connectivity and Tracking
Digitalisation of the deep renovation process and buildenvironment is enabled by ubiquitous connectivity andmonitoring of the environment itself, the artefacts andactors within it, and events that occur. Such monitoring iscritical for dynamic peak demand reduction andaffordability. Chapter 2 provides an overview of howcomputation capabilities are being integrated into thephysical environment and the role of sensor networks inthe context of deep renovation. The key advantages and
benefits of these technologies at the pre, during and post-renovation stages are discussed together with different
application use cases e.g. home automation vs buildinginfrastructure systems. The role and value of sensornetwork infrastructures and the legal and ethicalimplications of the use of such sensor infrastructures isalso discussed.
Chapter 3 – Building InformationModelling
Chapter 3 defines BIM and discusses the evolution of
building information modelling from computer-aided three-dimensional modelling to include time scheduling (4D) and
the next generation of BIM that integrates building designwith estimates and costing to provide a decision support
system for making reliable decisions across a building life-cycle. This chapter summarises the state-of-the-art on
BIM, with a specific emphasis on deep renovation, as wellas future trends for BIM solutions.
Chapter 4 – Simulation Simulation is a proven technique that uses computationalmathematical models to represent the physicalcharacteristics, expected or actual operation, and controlstrategies of a building and its energy systems. There aremany opportunities for using simulations across the deeprenovation life cycle including (1) integrating simulationswith other knowledge-based systems to support decisionmaking, (2) using simulations to evaluate and comparedesign scenarios, (3) integrating simulations with real-timemonitoring and diagnostic systems for building energymanagement and control, (4) integrating multiplesimulation applications, and (5) using VR to enable digitalbuilding design and operation experiences. While buildingperformance simulation is relatively well established, thereare numerous challenges to implementation across the lifecycle, not least integrating data from fragmented buildingsystems, modelling human-building interaction, amongstothers. Chapter 4 defines the building performancesimulation space outlining significant use cases, drivers foradoption and challenges for implementation.
Chapter 5 – Big Data and Analytics Similarly to a number of other industries, the constructionsector has been impacted and somewhat changed by thegrowing volume of heterogeneous data available atdifferent stages of the construction process. This trend isexpected to continue as technologies such as sensors andthe Internet of Things become more and more accessibleand commoditised. The availability of data is particularlyuseful in the context of deep renovation where it candramatically accelerate the decision making for buildingstock retrofit. Chapter 5 defines Big Data and analytics inthe context of deep renovation and describes how the useof Big Data and advanced analytics such as MachineLearning and Artificial Intelligence have impacted thedifferent stages of the deep renovation lifecycle.
Chapter 6 – Mobile Interfaces andAugmented Reality
As the technologies and the building elementsimplemented in deep renovation projects become moreadvanced and complex, there is growing need forspecialist skills and knowledge which may not be alwaysavailable on-site therefore reducing productivity andsafety. The use of mobile interfaces and augmented realitymay provide on-site operators with timely information andtherefore overcome some of these issues. Chapter 6explores the implications of the ever-increasing use ofmobile technologies in the deep renovation process with aparticular focus on augmented reality and the role it playsin the design as well as the implementation phase of thedeep renovation. Key drivers and barriers to adoption, andimplications for the workforce are also discussed.
Chapter 7 – 3D Scanning and DigitalTwinning
Chapter 7 introduces the role of digital twinning and 3Dscanning in the deep renovation lifecycle. Thesetechnologies are often confused with BIM and otherbuilding-related cyber-physical systems. This chapterstarts by defining digital twinning and constituenttechnologies and elements. Once defined, the state-of-artin both (i) the creation, and (ii) the use of digital twinningacross the deep renovation lifecycle is explored includingdrivers for adoption and barriers.
Chapter 8 - Additive manufacturing Chapter 8 defines and discusses the key elements andattributes of additive manufacturing and the role it plays indeep renovation projects. Additive manufacturing,including 3D printing, has potential opportunities for theconstruction industry and specific applications in the deeprenovation process. While additive manufacturing canprovide significant benefits in the deep renovation process,it is not without its own environmental footprint andbarriers. Upcoming technological advancements andtrends are discussed together with their potential impactfor different stakeholders.
Chapter 9 – Intelligent ConstructionEquipment and Robotics
The primary motivation behind the use of intelligentconstruction equipment and industrial exoskeletons is toprevent occupational injuries, human error, and associatedfinancial consequences. While these technologies offersignificant opportunities for the construction sector, theymay not be cost-effective, or suitable for complex,unpredictable and varied moves. Chapter 9 presents themain advantages and benefits of the use of cobots,exoskeletons, UAVs and other robotics technologies inconstruction and deep renovation contexts. It summarisesthe state-of-the-art of these technologies and current usecases. Operational, legal and ethical challenges toadoption and implementation are also discussed.
Chapter 10 - Open Access andInteroperability
Interoperability is one the technological barriers to deeprenovation. Deep renovation is a multi-domain area withmultiple inbound and outbound linkages to a wide varietyof stakeholders and systems. This results in significantinteroperability issues that impact data flows. Chapter 10discusses the concept of technological interoperability,and specifically data linking, across the deep renovationlifecycle. The state-of-the-art for addressing these issuesare discussed including advantages and limitations.
Chapter 11 - Security and DataPrivacy for Deep Renovation
Digitalisation during the deep renovation process willproduce significant volumes of data. Smart building andsmart home technologies assume massive increases inheterogeneous end-points with varying computationalcapabilities, intermittent connectivity and a wide variety ofpotentially conflicting data requirements, decisioncriticalities and priorities. Furthermore, it is envisaged thatmachine learning of increasing sophistication will be usedto make sense of this data in near-real time and, in somecases, actuate changes close to the edge of networks.Chapter 11 explores the security and data privacy issuesinherent in greater digitalisation of the deep renovationprocess and the built environment including vulnerabilitiesand threats associated with edge computing and edgeintelligence, and associated countermeasures.
Chapter 12 - Fintech for DeepRenovation and Smart Contracts
Access to capital is one of the key barriers for deeprenovation. This chapter presents the potential advantagesand benefits that financial technology (fintech) solutionssuch as crowdfunding, peer-to-peer lending and smartcontracts can provide to building owners and constructioncompanies in terms of financing. Future avenues forresearch in this space are also presented.
