A Closer Look into the Digitalisation & Transformation of Building Renovation
By RINNO
The urgent need to reduce the energy consumption and greenhouse gas emissions of buildings has brought deep renovation to the forefront of sustainable construction practices. In support of this effort, an international team of experts recently collaborated to produce an open-access book that delves into all things deep renovation. With contributions from experts across business, technology, and industry domains, RINNO’s ‘Disrupting Buildings’ defines a deep renovation digital ecosystem for the 21st century, offering valuable insights, identifying research opportunities, and charting a course for a more sustainable future in building construction and renovation.
The EU estimates that up to 75% of its existing building stock has poor energy performance, 85–95% of which will still be in use in 2050. RINNO is an EU-funded project working to accelerate the renovation rate of the EU building stock by reducing the time, effort, and cost of deep renovation projects while improving energy performance and stakeholder satisfaction. RINNO’s recently published book, “Disrupting Buildings: Digitalisation and the Transformation of Deep Renovation,” addresses what deep renovation is, its drivers and barriers, and the key technologies that enable deep renovation projects. Follow along as ‘Disrupting Buildings’ explores the pivotal role of Information and Communication Technologies (ICTs) in revolutionising construction, renovation, and maintenance, covering technologies like sensors, big data analytics, and Building Information Modelling (BIM).
Chapter 1: Definitions, Drivers, & Barriers of Deep Renovation
The deep renovation of existing buildings is essential for achieving climate goals particularly in the European Union, where buildings account for a significant portion of energy consumption and greenhouse gas emissions. Deep renovation offers numerous benefits beyond environmental sustainability. It enhances building quality, increases property value, improves energy security, and reduces energy poverty. Additionally, it creates employment opportunities, contributes to health and accessibility, and aligns with sustainability goals. Despite these benefits, deep renovation also faces barriers such as social norms, technological complexities, organisational challenges, and regulatory hurdles.
Read more on this chapter: Deep Renovation: Definitions, Drivers, & Barriers.
Chapter 2: Embedded Sensors, Ubiquitous Connectivity, & Tracking
Sensors and the Internet of Things (IoT) revolutionise construction and renovation by enabling real-time monitoring, enhancing efficiency, and safety. They’re crucial for smart buildings and homes, improving comfort and energy efficiency. Sensors optimise processes, boosting productivity and cost-effectiveness. However, addressing data management and ethical concerns is crucial to ensure their responsible and effective use.
Read more on this chapter: Embedded Sensors, Ubiquitous Connectivity, & Tracking
Chapter 3: Building Information Modelling
Building Information Modelling (BIM) is transforming construction and renovation processes by seamlessly integrating design, scheduling, cost management, and information structuring. It goes beyond mere 3D modelling, offering diverse advantages such as time scheduling, cost management, sustainability, and life cycle analysis. In particular, BIM addresses challenges in deep renovation projects by streamlining building condition assessment, information exchange, project scheduling, and budget management through advanced 4D and 5D BIM techniques, enhancing communication via simulations. Nevertheless, interoperability issues impede BIM’s integration across design software and project phases, necessitating manual interventions and underscoring the need for further development. While the fusion of BIM with artificial intelligence (AI) and machine learning (ML) shows potential for deep renovation interventions, the absence of comprehensive ontologies for renovation demands additional refinement.
Read more on this chapter: Building Information Modelling
Chapter 4: Building Performance Simulation
Building Performance Simulation (BPS) is essential for deep renovation. By using digital building replicas to evaluate real-life performance for decision-making, design assessment, and energy management, BPS predicts building behaviour to optimise energy efficiency. Through building simulation tools, BPS tests components and systems, identifies issues, evaluates design scenarios, and optimises thermal comfort and HVAC systems. Integration with knowledge-based systems improves decision-making, while real-time monitoring enhances energy management by modelling heat and mass transfers. However, challenges like usability, accuracy, interoperability, and BIM integration persist. While building simulation provides insights throughout the building life cycle, addressing integration and interoperability challenges in particular remains vital and requires advancements in big data handling solutions.
Read more on this chapter: Building Performance Simulation
Chapter 5: Big Data & Analytics in the Deep Renovation Life Cycle
Big data is revolutionising the renovation and construction sectors by facilitating data-driven decision-making. Existing use cases illustrate big data’s transformative role through technologies like BIM and platforms for waste management and smart road construction, alongside applications in flood detection and project delay prediction aided by deep learning. While offering advantages such as improved efficiency and reduced environmental impact, big data encounters challenges like security and organisational barriers, with future developments likely to focus on global commercialization and the integration of big data-driven BIM systems.
Read more on this chapter: Big Data and Analytics in the Deep Renovation Life Cycle
Chapter 6: Digital Twins & Their Roles in Building Deep Renovation Life Cycle
Digital twins are pivotal in the architecture, engineering, construction, and operations (AECO) sector and encapsulate physical assets and their virtual counterparts. The digital twin life cycle stretches across three stages: design, construction, and operation. In the design stage, the “foetal digital twin” emerges from conceptual plans and converging BIMs. Transitioning into the construction stage, the “child digital twin” incorporates as-built and as-performed information, facilitating progress monitoring and quality control. Finally, in the operation stage, the “adult digital twin” supports in-depth analysis of performance metrics post-construction. Despite diverse applications in progress monitoring and facilities management, challenges include the manual detection of geometric objects and a lack of labelled datasets. Addressing these challenges is essential to unlocking the potential of digital twins.
Read more on this chapter: Digital Twins & Their Roles in Building Deep Renovation Life Cycle
Chapter 7: Additive Manufacturing & The Construction Industry
Additive manufacturing (AM), or 3D printing, has reshaped renovation processes with its layer-based fabrication of complex structural components. AM brings environmental benefits by reducing material waste and CO2 emissions, while also streamlining processes and cutting costs through minimised labour and on-site assembly. However, challenges like high initial costs and regulatory concerns hinder its widespread adoption. Future research should focus on enhancing large-scale capabilities and material optimisation to drive smart, sustainable construction practices.
Read more on this chapter: Additive Manufacturing & the Construction Industry.
Chapter 8: Intelligent Construction Equipment & Robotics
Intelligent Construction Equipment and Robotics (IER) are reshaping the construction industry by addressing safety concerns, enhancing productivity, and mitigating the skilled labour shortage. Leveraging automation and robotics, IER improves safety by executing hazardous tasks and thus reducing accidents. It also boosts productivity by automating repetitive tasks and minimising human errors. Key applications include additive manufacturing, automated monitoring, UAVs for maintenance, robotic arms, and exoskeletons. Overall, while challenges like high costs and human-robot interactions persist, IER promises to revolutionise construction through safety, efficiency, and productivity enhancements.
Read more on this chapter: Intelligent Construction Equipment & Robotics.
Chapter 9: Cybersecurity Considerations for Deep Renovation
Despite the benefits of deep renovation, its integration with information technology (IT) and operational technology (OT) and the increasing use of autonomous equipment introduces cybersecurity concerns. The construction industry faces a growing threat of cybercrimes ranging from phishing to denial-of-service attacks, necessitating attention to safeguard automation and control systems and address vulnerabilities in building automation systems. Given the diverse landscape of construction firms and projects, a tailored contingency approach is essential to adapt cybersecurity measures to varying risk profiles and project scales. As such, a comprehensive cybersecurity strategy involving all stakeholders and stages of deep renovation projects becomes imperative to mitigate potential risks effectively.
Read more on this chapter: Cybersecurity Considerations for Deep Renovation
Chapter 10: Financing Building Renovation: Financial Technology as an Alternative Channel to Mobilise Private Financing
The chapter delves into the challenge of achieving long-term net-zero emissions, emphasising the crucial role of addressing energy inefficiency in buildings worldwide and particularly in the EU, where a significant portion of buildings require retrofitting and renovation. It discusses EU policy responses like the Energy Efficiency Directive of 2012 and its partial revision in 2018, highlighting the need for a comprehensive overhaul to align with the Renovation Wave strategy announced in 2020. The chapter also addresses financing challenges, noting limited resources as a major barrier, and advocating for well-targeted funding. It explores the potential of financial technology (FinTech) innovations, particularly crowdfunding and blockchain-based solutions, to mobilise private financing for building renovation projects, discussing their benefits, challenges, and empirical evidence from other sectors.
Read more on this chapter: Financing Building Renovation: Financial Technology as an Alternative Channel to Mobilise Private Financing
To learn more about deep renovation technologies in general, you can download the open-access book ‘Disrupting Buildings: Digitalisation and the Transformation of Deep Renovation’ for free. ‘Disrupting Buildings’ is a part of the Palgrave Studies in Digital Business & Enabling Technologies book series, which provides a comprehensive account of cloud computing, social media, mobile, big data, and other enabling technologies that are transforming how society operates and how people interact with each other. To read other works published in this series, click here.
References
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Arnesano, M., Mansi, S.A. (2023). Embedded Sensors, Ubiquitous Connectivity and Tracking. In: Lynn, T., Rosati, P., Kassem, M., Krinidis, S., Kennedy, J. (eds) Disrupting Buildings. Palgrave Studies in Digital Business & Enabling Technologies. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-031-32309-6_2
Doukari, O., Kassem, M., Greenwood, D. (2023). Building Information Modelling. In: Lynn, T., Rosati, P., Kassem, M., Krinidis, S., Kennedy, J. (eds) Disrupting Buildings. Palgrave Studies in Digital Business & Enabling Technologies. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-031-32309-6_3
Dimara, A., Krinidis, S., Ioannidis, D., Tzovaras, D. (2023). Building Performance Simulation. In: Lynn, T., Rosati, P., Kassem, M., Krinidis, S., Kennedy, J. (eds) Disrupting Buildings. Palgrave Studies in Digital Business & Enabling Technologies. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-031-32309-6_4
Koukaras, P., Krinidis, S., Ioannidis, D., Tjortjis, C., Tzovaras, D. (2023). Big Data and Analytics in the Deep Renovation Life Cycle. In: Lynn, T., Rosati, P., Kassem, M., Krinidis, S., Kennedy, J. (eds) Disrupting Buildings. Palgrave Studies in Digital Business & Enabling Technologies. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-031-32309-6_5
Pan, Y., Hu, Z., Brilakis, I. (2023). Digital Twins and Their Roles in Building Deep Renovation Life Cycle. In: Lynn, T., Rosati, P., Kassem, M., Krinidis, S., Kennedy, J. (eds) Disrupting Buildings. Palgrave Studies in Digital Business & Enabling Technologies. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-031-32309-6_6
Chougan, M., Al-Kheetan, M.J., Ghaffar, S.H. (2023). Additive Manufacturing and the Construction Industry. In: Lynn, T., Rosati, P., Kassem, M., Krinidis, S., Kennedy, J. (eds) Disrupting Buildings. Palgrave Studies in Digital Business & Enabling Technologies. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-031-32309-6_7
Pracucci, A., Vandi, L., RazaviAlavi, S. (2023). Intelligent Construction Equipment and Robotics. In: Lynn, T., Rosati, P., Kassem, M., Krinidis, S., Kennedy, J. (eds) Disrupting Buildings. Palgrave Studies in Digital Business & Enabling Technologies. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-031-32309-6_8
Sonkor, M.S., García de Soto, B. (2023). Cybersecurity Considerations for Deep Renovation. In: Lynn, T., Rosati, P., Kassem, M., Krinidis, S., Kennedy, J. (eds) Disrupting Buildings. Palgrave Studies in Digital Business & Enabling Technologies. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-031-32309-6_9
Cummins, M., Lynn, T., Rosati, P. (2023). Financing Building Renovation: Financial Technology as an Alternative Channel to Mobilise Private Financing. In: Lynn, T., Rosati, P., Kassem, M., Krinidis, S., Kennedy, J. (eds) Disrupting Buildings. Palgrave Studies in Digital Business & Enabling Technologies. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-031-32309-6_10
