Publications from the Centre for Advanced Built Environment Research (CABER)

This edited book addresses a gap in literature by advancing current understandings of the applications of immersive technology within the architecture, engineering, and construction (AEC) sector. Globally, the architecture, engineering and construction (AEC) sector makes an enormous contribution to the socio-economic development of nations, which is primarily evidenced by its creation/provision of the built environment. The sector has, however, often been criticised for inefficiencies, waste, and diverse forms of adverse impacts that are associated with the lifecycle of the provision of built assets – design, construction, operations & maintenance, and end-of-life phases. Over the years, the inefficiencies, waste and adverse impacts have often been a catalyst for calls and initiatives to transform the AEC sector. The advent of the fourth industrial revolution (commonly referred to as, ‘Industry 4.0’), which entails the automation and digitalisation of production, presents opportunities to leverage emerging technologies to improve the image and productivity of the sector. Prominent among the emerging technologies in the Industry 4.0 era is that of immersive technology, which includes virtual reality, mixed reality, and augmented reality. The capability of immersive technology to deliver beneficial impacts for multiple construction sector stakeholders throughout the construction lifecycle has been acknowledged within the industry and this continues to stimulate interest amongst practitioners, policymakers, and researchers. Despite this phenomenon, at present there is no dedicated compendium of research-informed text that focusses on the multifaceted applications of immersive technology throughout the lifecycle of the provision of built assets right from concept design to end-of-life. This book thus addresses this gap in literature by advancing current understanding of the applications of immersive technology within the AEC industry.  Readers will understand how the technologies are applied, the resulting array of impacts including benefits, drawbacks, challenges and future directions for applications, research, and development.

This Handbook presents opportunities, best practices, and case studies backed by cutting edge research on the drivers of continuous improvement of health, safety, and wellbeing in the architecture, engineering, construction, and facility management sector. The book consists of 23 chapters with six themes covering: ● Drivers of the business case for healthier and safer construction ● Opportunities and drivers of digital technologies for improving health and safety ● Drivers of human factors for improving health and safety ● Drivers of safer design and procurement ● Drivers of better health and wellbeing for construction. ● Opportunities for driving equality and inclusivity for safer construction. The book will be beneficial to academics, undergraduate and postgraduate (research and taught) students, professional institutions (such as the Institution of Occupational Safety and Health), health and safety professionals (health and safety officers, consultants and managers), occupational health professionals, mental health and wellbeing professionals, construction managers, architects, project professionals, engineers (design, construction, project, site, electrical, mechanical, civil, building services, and structural), facilities managers, quantity surveyors, and site managers. The aim of the book is to provide critical perspectives alongside evidence based practical examples of success stories, that should inspire readers and engender continuous improvement in health, safety, and wellbeing in the construction industry.

Pushing the boundaries of flood risk management research, this comprehensive Research Handbook presents pragmatic insights into all areas relating to flood risk. Through its use of dynamic and people-centred paradigms, it explores urban flood management within localities, properties, neighbourhoods and cities. Structured around the flood risk management cycle, chapters explore the critical importance of managing the consequences of flooding whilst examining key concepts such as mitigation, preparedness, emergency management and recovery. An international range of expert contributors from an array of disciplines recognize the inadequacies of existing governance approaches and mechanisms when it comes to addressing urban flooding, and identify the ways in which these can be strengthened in order to create an integrated flood and water management framework. Adopting a forward-thinking approach, the Research Handbook also investigates future directions of flood risk management research. The Research Handbook on Flood Risk Management will be an indispensable resource for academics, researchers and students interested in environmental geography, environmental governance and regulation, urban studies, politics and public policy, and the management of natural resources.

This handbook explores the critically important topic of embodied carbon, providing advanced insights that focus on measuring and reducing embodied carbon from across the built environment, including buildings, urban areas and cities, and construction materials and components. Split into five distinct sections, international experts, researchers, and professionals present the recent developments in the field of embodied carbon from various perspectives and at different scales of material, building, and city. Following an introduction to the embodied carbon question, the chapters in Section 1 then cover the key debates around issues such as the politics of embodied carbon, links between embodied carbon and thermal mass, and the misuse of carbon offsets. Section 2 reviews the embodied carbon policies in a selected number of countries. Sections 3, 4, and 5 approach the topic of embodied carbon from urban-, building-, and material-scale perspectives, respectively, and use case studies to demonstrate estimation techniques and present opportunities and challenges in embodied carbon mitigation. This will be important reading for upper-level students and researchers in Architecture, Urban Planning, Engineering, and Construction disciplines. Presenting case studies of embodied carbon assessment, this book will also help practicing architects, engineers, and urban planners understand embodied carbon estimation techniques and different mitigation strategies.

This edited book presents a significant and timely contribution to our understanding of a broad range of issues pertaining to COVID-19 and its relationship to occupational safety, health and well-being (OSHW) in the global construction industry. The editors first introduce the industry and its poor OSHW history before highlighting some of the broader impacts of the pandemic on the sector. The book is then divided into two sections. Section One focuses on the management of COVID-19 transmission risk. It captures insights, practices, technologies and lessons learned in relation to what has and is being done to prevent or mitigate the risk of COVID-19 transmission among the construction workforce. Construction Safety, Health and Well-being in the COVID-19 Era also details case studies, lessons and best practices for managing sites and workforces when infections inevitably do occur. Section Two brings together international chapters discussing the impacts of COVID-19 on the OSHW of the construction workforce both on and off-site, as well as the management of those impacts. Furthermore, this presents implications of the pandemic (at the short-, medium-, and long-term) for other performance measures of construction projects such as cost, schedule, quality and, most importantly, how the pursuit/non-pursuit of such performance measures have impacted/will impact the OSHW of construction workers and professionals in the industry. This book addresses the gap in literature by offering global perspectives on the OSHW impacts and implications of COVID-19 in the construction industry and will help its wide readership (including construction industry organisations, professionals, researchers, government bodies/policy makers and students) to understand a broad suite of issues pertaining to COVID-19 and its relationship to OSHW in construction.

High-Performance Computing (HPC) is increasingly recognised as a critical enabler of advanced modelling, simulation, and data-intensive research. However, its adoption within the built environment remains limited compared to more established computational domains. This paper presents a user-centred investigation into the barriers and opportunities associated with HPC adoption in the built environment, drawing on qualitative data from a stakeholder workshop involving 20 participants, supported by Mentimeter-based interactive polling and analysis of workshop discussions. The findings reveal a persistent gap between the perceived relevance and practical use of HPC. While participants recognised its potential for applications such as digital twins, infrastructure simulation, and data-driven design, adoption was constrained by complex access processes, limited training, and poor interoperability with tools such as Building Information Modelling (BIM), Geographic Information Systems (GIS), and Computer-Aided Design (CAD). Additional barriers included data governance challenges, intellectual property concerns, and limited trust in shared computational environments. The findings demonstrate that HPC adoption is not solely a technical issue, but a socio-technical challenge shaped by organisational practices, institutional structures, and user capabilities. In response, the paper proposes a user-centred roadmap for inclusive HPC adoption in the built environment. Key priorities include simplifying access pathways, developing domain-specific training, improving interoperability, and strengthening governance frameworks. The study contributes practical insights to support more accessible and inclusive digital research infrastructure and informs the development of the National Federated Compute Services (NFCS) roadmap for interoperable HPC adoption within the built environment sector.

Corruption in Africa’s construction and energy sectors raises project costs, delays delivery and weakens trust in public institutions and financiers. These governance failures constrain the continent’s ability to close its infrastructure delivery gap and meet climate and development goals. This study examines whether a statutory duty of good faith, embedded within collaborative legal frameworks, can operate as a governance instrument to reduce adversarial behaviour, curb corruption and strengthen infrastructure delivery in African construction and energy sectors. The study adopts an interpretivist qualitative design, combining a literature review with fourteen semi-structured interviews with construction, infrastructure and energy professionals. The sample includes practitioners with experience of African project delivery and others working in governance environments comparable to those found across the continent. Data were thematically analysed using an evaluative framework developed inductively from the data and subsequently structured to categorise levels of support. Practitioners view good faith as a practical governance tool. Interviewees linked a statutory duty of good faith to clearer expectations regarding transparency, payment discipline, procurement integrity, dispute resolution and alignment with multilateral development bank (MDB) and development finance institution (DFI) safeguard standards. Seven collaborative legal measures are identified that translate good faith into an actionable reform agenda. Codifying good faith, supported by harmonised legal frameworks, streamlined procurement, improved transparency, fair payment protections and stronger regulatory oversight, could reduce governance risk and make African infrastructure sectors more attractive to concessional and private capital. Realising these benefits will require phased and context-specific implementation and sustained investment in institutional capacity.

Damp in buildings is a major contributor to structural deterioration, microbial growth, and poor indoor air quality. Conventional detection methods rely heavily on manual inspections and simple threshold-based analyses, making them largely reactive and ineffective for early intervention. This study introduces an artificial intelligence (AI)-driven framework for proactive damp monitoring and prediction, powered by humidity sensor data and enhanced through Agentic Retrieval-Augmented Generation (Agentic RAG) and Large Language Models (LLMs). The framework conducts comprehensive time-series analysis, including humidity trend extraction, anomaly detection, AutoRegressive Integrated Moving Average (ARIMA)-based forecasting, and sensor reliability evaluation through distributional assessment and missing-data analysis. Agentic RAG extends traditional RAG by enabling autonomous task planning and adaptive reasoning, allowing LLMs to dynamically retrieve context, interpret sensor behaviour, and generate clear, human-readable diagnostic insights. A key design principle is computational sustainability: the system reuses existing open LLMs within lightweight agentic pipelines, avoiding energy-intensive model retraining and supporting cost-efficient deployment in practical settings. Visual outputs, such as trend plots, anomaly markers, and reliability heatmaps, provide transparent and interpretable evidence for decision-making. Results from real-world humidity datasets demonstrate the framework's effectiveness in identifying gradual moisture buildup, forecasting high-risk damp conditions, and pinpointing faulty sensors with high accuracy. By combining Agentic RAG with reusable LLM components, the proposed approach transforms raw humidity data streams into contextual, actionable intelligence, advancing predictive maintenance while promoting sustainable and scalable building health management.

The rapid advancement of Large Language Models (LLMs) is creating new opportunities for intelligent automation, forecasting, and decision-making in Smart Grids and Renewable Energy (SGRE) systems. This paper provides a comprehensive review of recent LLM-based developments across 15 functional domains, spanning forecasting, control, diagnostics, energy policy, and market strategy. Analysing more than 60 peer-reviewed studies, the review identifies key methodological trends, including the prominence of Generative Pre-trained Transformer (GPT)-based models, LLaMA variants, and Retrieval-Augmented Generation (RAG)-enhanced pipelines, and documents their reported gains in predictive accuracy, operational efficiency, and decision support. Quantitative mapping shows that current research is heavily concentrated on Forecasting and Automation, while critical areas such as Trustworthiness, Federated Learning, and System Reliability remain underexplored. The study also outlines emerging directions involving hybrid, interpretable, and energy-efficient LLM architectures that incorporate Multi-agent Reasoning and Human-in-the-loop control. Overall, the findings indicate that LLMs are evolving from general language processors into cognitive energy assistants capable of supporting autonomous, sustainable, and resilient next-generation smart grid systems.

Air quality (AQ) decision support systems use data and models to guide actions, reduce exposure, and protect public health. Large language models (LLMs) emerge as powerful tools in this field, integrating diverse data, generating interpretable insights, and enabling natural language (NL) interaction. This study provides the first comprehensive synthesis of how LLMs are shaping AQ decision support, covering methods, tools, applications, and datasets. Three key themes emerge: (1) LLMs are improving a growing range of AQ decision tasks, showing performance gains over traditional methods; (2) critical risks, such as data bias, hallucinations, and opacity, must be mitigated to ensure trust and reliability; and (3) gaps remain in benchmarking, real-world validation, and policy integration. Evidence suggests LLMs can enhance forecasts, regulatory guidance, and public access to AQ information. However, progress depends on standardised evaluation, field validation, ethical safeguards, and sustainable, energy-efficient model use. Together, these elements point toward more effective, transparent, and sustainable AQ decision support systems.