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Abstract Sustainable construction is a challenging prospect in Gulf countries such as Saudi Arabia and the use of Building Information Modelling (BIM) is often suggested as a solution. However, achieving improvement is associated with considerable challenges, particularly regarding energy efficiency improvements. Furthermore, the extreme environmental conditions in Saudi Arabia increase the demand for energy. As energy consumption in buildings is one of the main problems related to the built environment in both dry and hot climates, although in hot climates especially the issue is exacerbated by the particularly great need for cooling systems in buildings. On the other hand, one of the most important factors that affect Saudi Arabia’s building design is gender and function, demonstrating how the culture of Saudi Arabia, significantly influenced by the Islamic religion, affects design. This paper aims to present a literature review of the area of sustainable building design and the impact of cultural issues, focusing on the case of Saudi Arabia. This paper has analysed related literature in the area of sustainable building design and the influence of cultural issues, focusing on the case of Saudi Arabia. This review has identified the lack of using technology to support designs in Saudi Arabia, lack of achieving sustainability in Saudi Arabia, culture issues effect on designing in Saudi Arabia, and lack of using Building Information Modelling (BIM) in Saudi Arabia for both public and private project. These issues have led to a series of recommendations that have the potential to improve the adoption of sustainable design in Saudi Arabia by using (BIM). Some of these recommendations are developing and understanding the influence of cultural issues on achieving sustainable design. Secondly, analysing the different viewpoints on sustainability between the experts and members of the public. Furthermore, developing a framework of measures of sustainable design for buildings with consideration of specific factors. Additionally, showing the current level of using BIM technologies. Finally, developing a methodology, supported by BIM, for both government and private projects.

Many seaports are facing increasing pressure to reduce their carbon footprint, while increasing their energy efficiency and global competitiveness. Moreover, energy consumption in seaports is continuously monitored to manage the increasing energy costs, these rising costs are reflected in the increased fuel demand. The fishing industry is one of the most energy intensive activity at seaports. In addition, the global human consumption of fish increased dramatically from 1950 to 2012. This paper will develop a roadmap to convert fishing ports into carbon-free ports. A number of techniques and methodologies will be used to analyze energy consumption in the port and buildings, and will include sustainability informed decision making. The overall objective of the net-zero port is to reduce energy dependence from the national grid by taking advantage of the electricity produced locally from solar energy. The roadmap that we have developed will contribute to the emergence of carbon-free fishery port ecosystem that can implement sustainable energy practices, including an assessment of the quality of the energy used in the fishery port and informed practices for promoting carbon-free societies.

It is highly demanding and challenging to maximise the stiffness of the interpenetrating phase composites (IPCs) while still keeping their isotropy. In this paper, the elastic properties of IPCs reinforced by three different types of regular lattice fibre networks are investigated by computer simulation and analytical methods. The numerical results indicate that the larger the difference between the Poisson’s ratios and the smaller the difference between the Young’s moduli of the constituent materials, the larger the Young’s moduli of these IPCs are. It is also found that structural hierarchy can enhance the stiffness of these IPCs by 30%. In addition, the three types of IPCs have Zener anisotropy factors in the range of 1.0±0.04 in most cases, could have an almost isotropic Young’s modulus two times larger than the Voigt limit, and a Poisson’s ratio with a positive or negative or zero value. Moreover, they are easy to manufacture, their Young’s moduli are in general 1.0–3.0 times those of the conventional particle or short fibre reinforced composites and other types of IPCs including those reinforced by the triply periodic minimal surface (TPMS) shells, and the type of IPCs with the largest Young’s modulus has been identified.

To achieve the potential of smart cities, there is a strong requirement to use a set of useful, but still accessible services within smart city systems. Interoperability challenges and roadblocks for software developers and integrators are well-known consequences of fragmented semantics across different contexts. Furthermore, in the smart city context, there is a need to ensure the security and identity of real-world services operating on this data through the adoption of access control principles (authorization and authentication). The use of ontologies to unify the diverse semantics of multiple domains is one strategy that has had considerable success in the past. This paper describes an access management ontology in smart cities developed to enable the interoperability of physical built environment assets, sensing and actuation devices and current built environment services with existing security standards, digital twin and Building Information Model (BIM) datasets. It also provides interoperability between user interfaces and the actors who use them in the context of establishing an access management in smart cities framework for the built environment. This has been validated through its implementation in the Cardiff Urban Sustainability Platform (CUSP), deployed to manage a variety of smart services on a university campus. This validation has successfully shown the ability of the ontology to function as intended in the context of a digital twin, thereby offering single sign-on and suitable access control.

The Irish Seafood agency reports that 15% of global energy is consumed by operations related to refrigeration and air conditioning in the fish industry which stresses the importance of integration with clean renewables and adoption of smart energy management solutions. While fish processing industries have high energy costs with continuous refrigeration, air conditioning and ice making processes, there is a real need to analyse and model energy use in fish ports to understand environmental impacts in terms of CO2 emissions while exploring the potential for integrating renewable energy sources.In this paper, we conduct energy modelling and optimization for the Milford Haven fish processing port in South Wales. We explain how a simulation capability can be developed at the fish industry port level and propose a simulation-based optimization strategy to determine optimized schedules for appliances. The results show that energy consumption can be reduced with the use of optimized appliance schedules developed in relation to the total energy demand as well as a wide range of optimization constraints. Keywords: Energy analysis, Energy modelling, Simulation, Optimization, Renewable energy, Scheduling appliances

With the rapid growth in clean distributed energy resources involving micro-generation and flexible loads, users can actively manage their own energy and have the capability to enter in a market of energy services as prosumers while reducing their carbon footprint. The coordination between these distributed energy resources is essential in order to ensure fair trading and equality in resource sharing among a community of prosumers. Peer-to-Peer (P2P) networks can provide the underlying mechanisms for supporting such coordination and offer incentives to prosumers to participate in the energy market. In particular, the federation of energy clusters with P2P networks has the potential to unlock access to energy resources and lead to the development of new energy services in a fast-growing sharing energy economy. In this paper, we present the formation and federation of smart energy clusters using P2P networks with a view to decentralise energy markets and enable access and use of clean energy resources. We implement a P2P framework to support the federation of energy clusters and study the interaction of consumers and producers in a market of energy resources and services. We demonstrate how energy exchanges and energy costs in a federation are influenced by the energy demand, the size of energy clusters and energy types. We conduct our modelling and analysis based on a real fish industry case study in Milford Haven, South Wales, as part of the EU H2020 INTERREG piSCES project.

Marine activities in seaports account for circa 3% of total carbon emissions worldwide, prompting several initiatives to decarbonise their energy systems and make seaports smarter and greener. This paper provides a thorough and authoritative review of the vast array of research in this field, including past and ongoing initiatives. The study reveals that existing research leverages recent ad-vances in digital technologies while focusing on one or several of the following themes: carbon reduction, use of renewable energy resources, cost-performance optimisation, deployment of smart control technologies, the regulatory land-scape for greening seaports, and implementing green port practices guidelines. As such, the paper provides a critical review of existing technologies and con-cepts that promote and contribute to the decarbonisation of seaports, including Smart Grids and Virtual Power Plants. Several avenues for future research are then discussed, including (a) total life cycle approach to seaport energy manage-ment, (b) Semantic-based modelling, forecasting and optimisation of seaports energy systems, (c) Secure and reliable seaports energy services, and (d) Transi-tion towards prosumer-driven seaport energy communities. The paper concludes by emphasising the importance of an adapted energy regulatory landscape at a national and EU-wide level to meet EU phased energy reduction targets.

Integrating data analytics, optimisation and dynamic control to support energy services has seen significant interest in recent years. Larger appliances used in an industry context are now provided with Internet of Things (IoT)-based interfaces that can be remotely monitored, with some also provided with actuation interfaces. The combined use of IoT and edge computing enables connectivity between energy systems and infrastructure, providing the means to implement both energy efficiency/optimisation and cost reduction strategies. We investigate the economic implications of harnessing IoT and edge/cloud technologies to support energy management for HVAC (Heating, Ventilation and Air Conditioning) systems in buildings. In particular, we evaluate the cost savings for building operations through energy optimisation. We use a real use case for energy optimisation as identified in the EU “Sporte2” project (focusing on the energy optimisation of sports facilities) and explore several scenarios in relation to costs and energy optimisation.

The construction sector faces the urgent need to prioritize energy efficiency due to an increasingly stringent regulatory landscape in response to the climate change agenda. Central to this transition is the pivotal role of education in equipping professionals with the necessary knowledge and skills. Educational solutions have emerged as powerful tools for promoting awareness and interventions to mitigate climate change. This article provides a case study that highlights the successful utilisation of computer technology in delivering digital solutions to advance energy education and promote more informed energy practices in the construction industry. The utilisation of digital technologies can enhance collaborative efforts in energy efficiency training, which is of critical significance in ensuring the security, sovereignty, transparency, immutability, and decentralisation of interventions related to energy education. This paper presents a framework that utilises Blockchain technology to facilitate training labelling and authenticity based on smart contracts and mobile passports to provide a secure and efficient solution for the delivery of training and education in the energy domain. Our research examines the challenges and opportunities related to energy efficiency training within the construction industry. By integrating industry-specific insights, exemplifications, and case studies, we provide an in-depth understanding of the interconnection between energy efficiency education and digital solutions with the unique context of the construction industry. We underscore the importance of leveraging digital platforms as educational tools to foster a deeper understanding and adoption of energy-efficient practices. We demonstrate that educational solutions play a pivotal role in driving awareness and interventions for mitigating climate change, greatly empowering individuals and organizations to adopt energy-efficient practices and to address sustainability objectives.

This research extends Hasan Fathy’s (1986) principle of vernacular architecture by focusing on the Rawshan through an investigation of two criteria: aesthetics and energy efficiency. The paper discusses the views of both the Saudi public and key decision-makers on reviving vernacular architecture in the context of Saudi Arabia’s rapidly developing economy, characterized by relatively high rates of energy consumption and CO2 emissions. This research explores (a) the interaction in domestic buildings of Saudi occupants with their windows, and how these are perceived as an interface with the external environment; (b) awareness and knowledge of the use of shading elements (such as Rawshans) to reduce the use of artificial lighting while maintaining indoor privacy; (c) Saudi awareness of, and familiarity with, the Rawshan as a vernacular element and a secular architectural tradition; and (d) Saudi views on the revival of traditional architectural elements with a focus on the Rawshan. An online survey (n = 812) was conducted across Saudi Arabia complemented by interviews with expert decision-makers (n = 23) to (a) assess criteria such as privacy, aesthetics, daylight, ventilation, and energy consumption in Saudi residences and (b) investigate the level of acceptance of an optimized retrofitted Rawshan design.

Air quality and energy consumption are among the top ten environmental priorities in seaports as stated by the European Sea Ports Organization. Globally, it is estimated that 15% of energy consumption can be attributed to refrigeration and air conditioning systems in fishing activities. There is a real need to understand energy usage in fishery ports to help identify areas of improvements, with a view to optimize energy usage and minimize carbon emissions. In this study, we elaborate on ways in which a simulation capability can be developed at the community level with a fishery port, using a real-world case study seaport in Milford Heaven (Wales, UK). This simulation-based strategy is used to investigate the potential of renewable energy, including local solar farms, to meet the local power demand. This has informed the development of a simulation-based optimization strategy meant to explore how smart energy communities can be formed at the port level by integrating the smart grid with the local community energy storage. The main contribution of the paper involves a co-simulation environment that leverages calibrated energy simulation models to deliver an optimization capability that (a) manages electrical storage within a district an environment, and (b) promotes the formation of energy communities in a fishery port ecosystem. This is paving the way to policy implications, not only in terms of carbon and energy reduction, but also in the formation and sustained management of energy communities.

The development of new climate change policies has increased the motivation to reduce energy use in buildings, as reflected by a stringent regulatory landscape. The construction industry is expected to adopt new methods and strategies to address such requirements, focusing primarily on reducing energy demand, improving process efficiency and reducing carbon emissions. However, the realisation of these emerging requirements has been constrained by the highly fragmented nature of the industry, which is often portrayed as involving a culture of adversarial relationships and risk avoidance, which is exacerbated by a linear workflow. Recurring problems include low process efficiency, delays and construction waste. Building information modelling (BIM) provides a unique opportunity to enhance building energy efficiency (EE) and to open new pathways towards a more digitalised industry and society. BIM has the potential to reduce (a) waste and carbon emissions, (b) the endemic performance gap, (c) in-use energy and (d) the total lifecycle impact. BIM also targets to improve the whole supply chain related to the design, construction as well as the management and use of the facility. However, the construction workforce is required to upgrade their skills and competencies to satisfy new requirements for delivering BIM for EE. Currently, there is a real gap between the industry expectations for employees and current training and educational programmes. There is also a set of new requirements and expectations that the construction industry needs to identify and address in order to deliver more informed BIM for EE practices. This paper provides an in-depth analysis and gap identification pertaining to the skills and competencies involved in BIM training for EE. Consultations and interviews have been used as a method to collect requirements, and a portfolio of use cases have been created and analysed to better understand existing BIM practices and to determine current limitations and gaps in BIM training. The results show that BIM can contribute to the digitalisation of the construction industry in Europe with adapted BIM training and educational programmes to deliver more informed and adapted energy strategies.

Predictive analytics play a significant role in ensuring optimal and secure operation of power systems, reducing energy consumption, detecting fault and diagnosis, and improving grid resilience. However, due to system nonlinearities, delay, and complexity of the problem because of many influencing factors (e.g., climate, occupants’ behaviour, occupancy pattern, building type), it is a challenging task to get accurate energy consumption prediction. This paper investigates the accuracy and generalisation capabilities of deep highway networks (DHN) and extremely randomized trees (ET) for predicting hourly heating, ventilation and air conditioning (HVAC) energy consumption of a hotel building. Their performance was compared with support vector regression (SVR), a most widely used supervised machine learning algorithm. Results showed that both ET and DHN models marginally outperform the SVR algorithm. The paper also details the impact of increasing the deep highway network’s complexity on its performance. The paper concludes that all developed models are equally applicable for predicting hourly HVAC energy consumption. Possible reasons for the minimum impact of DHN complexity and future research work are also highlighted in the paper.

Smart building monitoring demands a new software infrastructure that can elaborate building domain knowledge in order to provide advanced and intelligent functionalities. Conventional facility management (FM) software tools lack semantically rich components, and that limits the capability of supporting software for automatic information sharing, resource negotiation and to assist in timely decision making. Recent hardware innovation on compact ZigBee sensor devices, software developments on ontology and intelligent software agent paradigms provide a good opportunity to develop tools that can further improve current FM practices. This paper introduces an integrated framework which includes a ZigBee based sensor network and underlying multi-agent software (MAS) components. Several different types of sensors were integrated with the ZigBee host devices to produce compact multi-functional sensor units. The MAS framework incorporates the belief-desire-intention (BDI) abstraction with ontology support (provided via explicit knowledge bases). The different software agent types have been developed to work with sensor hardware to conduct resource negotiation, to optimize battery utilization, to monitor building space in a non-intrusive way and to reason about its usage through real time ontology model queries. The deployed sensor network shows promising intelligent characteristics, and it has been applied in several on-going research projects as an underlying decision making service. More applications and larger deployments have been planned for future work.

Reducing carbon emissions and addressing environmental policies in the construction domain has been intensively explored with solutions ranging from energy efficiency techniques with building informatics to user behavior modelling and monitoring. Such strategies have managed to improve current practices in managing buildings, however decarbonizing the built environment and reducing the energy performance gap remains a complex undertaking that requires more comprehensive and sustainable solutions. In this context, building information modelling (BIM), can help the sustainability agenda as the digitalization of product and process information provides a unique opportunity to optimize energy-efficiency-related decisions across the entire lifecycle and supply chain. BIM is foreseen as a means to waste and emissions reduction, performance gap minimization, in-use energy enhancements, and total lifecycle assessment. It also targets the whole supply chain related to design, construction, as well as management and use of facilities, at the different qualifications levels (including blue-collar workers). In this paper, we present how building information modelling can be utilized to address energy efficiency in buildings in the operation phase, greatly contributing to achieving carbon emissions targets. In this paper, we provide two main contributions: (i) we present a BIM-oriented methodology for supporting building energy optimization, based on which we identify few training directions with regards to BIM, and (ii) we provide an application use case as identified in the European research project “Sporte2” to demonstrate the advantages of BIM in energy efficiency with respect to several energy metrics.

This study presents a model for district-level electricity demand forecasting using a set of Artificial Neural Networks (ANNs) (parallel ANNs) based on current energy loads and social parameters such as occupancy. A comprehensive sensitivity analysis is conducted to select the inputs of the ANN by considering external weather conditions, occupancy type, main income providers’ employment status and related variables for the fuel poverty index. Moreover, a detailed parameter tuning is conducted using various configurations for each individual ANN. The study also demonstrates the strength of the parallel ANN models in different seasons of the years. In the proposed district level energy forecasting model, the training and testing stages of parallel ANNs utilise dataset of a group of six buildings. The aim of each individual ANN is to predict electricity consumption and the aggregated demand in sub-hourly time-steps. The inputs of each ANN are determined using Principal Component Analysis (PCA) and Multiple Regression Analysis (MRA) methods. The accuracy and consistency of ANN predictions are evaluated using Pearson coefficient and average percentage error, and against four seasons: winter, spring, summer, and autumn. The lowest prediction error for the aggregated demand is about 4.51% for winter season and the largest prediction error is found as 8.82% for spring season. The results demonstrate that peak demand can be predicted successfully, and utilised to forecast and provide demand-side flexibility to the aggregators for effective management of district energy systems.

Recent building emergency management research has highlighted the need for the effective utilization of dynamically changing building information. BIM (building information modelling) can play a significant role in this process due to its comprehensive and standardized data format and integrated process. This paper introduces a BIM based virtual environment supported by virtual reality (VR) and a serious game engine to address several key issues for building emergency management, for example, timely two-way information updating and better emergency awareness training. The focus of this paper lies on how to utilize BIM as a comprehensive building information provider to work with virtual reality technologies to build an adaptable immersive serious game environment to provide real-time fire evacuation guidance. The innovation lies on the seamless integration between BIM and a serious game based virtual reality (VR) environment aiming at practical problem solving by leveraging state-of-the-art computing technologies. The system has been tested for its robustness and functionality against the development requirements, and the results showed promising potential to support more effective emergency management.

Sustainability ill-practices in the construction industry can have major drawbacks on meeting governmental targets on carbon and energy reduction. Using a mixed-method approach drawn from three studies to explore the level of engagement of construction stakeholders in adopting government sustainability agendas, the research identifies a wide range of perceived barriers, which operate broadly at ‘individual’ and ‘organisational’ levels. Sustainability knowledge in construction is fragmented, diverse, embedded in various documents, and developed in a non-concerted and integrated way across stakeholders, localities, regions, and countries. There is an emergent need for a socio-technical ‘knowledge solution’ to create circles of impacts that bind building professionals, energy administrations, and citizens in a shared sustainability experience to address a number of issues.

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.