Purpose: This paper reviews the state-of-the art research in life cycle assessment (LCA) applied to buildings. It focuses on current research trends, and elaborates on gaps and directions for future research. Methods: A systematic literature review was conducted to identify current research and applications of LCA in buildings. The proposed review methodology includes (i) identifying recent authoritative research publications using established search engines, (ii) screening and retaining relevant publications, and (iii) extracting relevant LCA applications for buildings and analyzing their underpinning research. Subsequently, several research gaps and limitations were identified, which have informed our proposed future research directions. Results and discussions: This paper argues that humans can attenuate and positively control the impact of their buildings on the environment, and as such mitigate the effects of climate change. This can be achieved by a new generation of LCA methods and tools that are model based and continuously learn from real-time data, while informing effective operation and management strategies of buildings and districts. Therefore, the consideration of the time dimension in product system modeling is becoming essential to understand the resulting pollutant emissions and resource consumption. This time dimension is currently missing in life cycle inventory databases. A further combination of life cycle impact assessment (LCIA) models using time-dependent characterization factors can lead to more comprehensive and reliable LCA results. Conclusions and recommendations: This paper promotes the concept of semantic-based dynamic (real-time) LCA, which addresses temporal and spatial variations in the local built and environmental ecosystem, and thus more effectively promotes a “cradle-to-grave-to-reincarnation” environmental sustainability capability. Furthermore, it is critical to leverage digital building resources (e.g., connected objects, semantic models, and artificial intelligence) to deliver accurate and reliable environmental assessments.

Augmented and virtual reality have the potential to provide a step-change in productivity in the construction sector; however, the level of adoption is very low. This paper presents a systematic study of the factors that limit and drive adoption in a construction sector–specific context. A mixed research method was employed, combining qualitative and quantitative data collection and analysis. Eight focus groups with 54 experts and an online questionnaire were conducted. Forty-two limiting and driving factors were identified and ranked. Principal component analysis was conducted to group the identified factors into a smaller number of factors based on correlations. Four types of limiting factors and four types of driving factors were identified. The main limitation of adoption is that AR and VR technologies are regarded as expensive and immature technologies that are not suitable for engineering and construction. The main drivers are that AR and VR enable improvements in project delivery and provision of new and better services. This study provides valuable insights to stakeholders to devise actions that mitigate the limiting factors and that boost the driving factors. This is one of the first systematic studies to present a detailed analysis of the factors that limit and drive adoption of AR and VR in the construction industry. The main contribution of this study is that it grouped and characterized myriad limiting and driving factors into easily understandable categories, so that the limiting factors can be effectively mitigated and the driving factors potentiated. A roadmap with specific short-term and medium-term actions for improving adoption was outlined.

Built environment data is of varying nature embedding various forms of sensitivities with potential legal, contractual, intellectual property, and security implications. The paper presents a governance approach for managing multi-actor, multi-discipline, and total lifecycle data, informed by a wide industry consultation conducted in the UK between March and September 2011. The study identifies a number of barriers in engaging with Building Information Modelling (BIM) efforts with a view of facilitating collaboration around a common and integrated project specification. A governance model is proposed that addresses the identified adoption blockers underpinned by a “mixed approach”, that factors in various modes of information delivery, ranging from paper-based documents to object-based information conveyed by IFC (Industry Foundation Classes). A demonstrator system is developed and used to validate our BIM governance concepts. Our governance model is discussed in the context of the recent UK government BIM industry consultation document supported by a research and development (R&D) roadmap taking into account current industry structure and its various levels of stakeholders’ maturity, capability and readiness.

Recent technological developments in the construction industry are seeking to create smart cities by using Cyber-Physical Systems (CPSs) to enhance information models such as BIM. Currently, BIM models are commonly adopted to work with IoT-based systems and embrace smart technologies that offer interoperability in the communication layer. In future, it is envisioned that digital twins will provide new possibilities for cyber-physical systems via monitoring and simulation. However, rarely in this rapidly developing field is security fully considered. This paper reviews the relevant literature regarding the use of the IoT in the built environment and analyses current practices. It also presents examples of cities that use the IoT to improve construction and the lived experience. Finally, it reviews how digital twins factor in multiple layers defined in CPSs, from physical objects to information models. Based on this review, recommendations are provided documenting how BIM specifications can be expanded to become IoT compliant, enhancing standards to support cybersecurity, and ensuring digital twin and city standards can be fully integrated in future secure smart cities.

Potable water distribution networks (WDNs) and wastewater collection networks (WWCNs) are the two fundamental constituents of the complex urban water infrastructure. Such water networks require adapted design interventions as part of retrofitting, extension, and maintenance activities. Consequently, proper optimization methodologies are required to reduce the associated capital cost while also meeting the demands of acquiring clean water and releasing wastewater by consumers. In this paper, a systematic review of the optimization of both WDNs and WWCNs, from the preliminary stages of development through to the state-of-the-art, is jointly presented. First, both WDNs and WWCNs are conceptually and functionally described along with illustrative benchmarks. The optimization of water networks across both clean and waste domains is then systematically reviewed and organized, covering all levels of complexity from the formulation of cost functions and constraints, through to traditional and advanced optimization methodologies. The rationales behind employing these methodologies as well as their advantages and disadvantages are investigated. This paper then critically discusses current trends and identifies directions for future research by comparing the existing optimization paradigms within WDNs and WWCNs and proposing common research directions for optimizing water networks. Optimization of urban water networks is a multidisciplinary domain, within which this paper is anticipated to be of great benefit to researchers and practitioners.