Building optimisation techniques provide a rigorous framework for exploring new optimal design solutions. In this study, a genetic algorithm (GA) was used to investigate the energy efficiency of a vernacular architectural element (Rawshan) in Saudi Arabia. Two objectives were optimised using a GA simulation enhanced: energy consumption optimisation and useful daylight illuminance (UDI) optimisation. A calibrated simulation model of a typical house in Saudi Arabia was used in the study. Several metrics, such as light interference from shadows or other windows, were considered to indicate the importance of the Rawshan. Computational studies were performed using different climatic conditions, and the results were compared with and without a Rawshan element using the weather data of Mecca, Jeddah, Riyadh, and Al-Baha. In this study, the blind thicknesses on the front and sides of the Rawshan were used as optimisation variables. The results showed that using a GA with energy consumption as an objective can reduce energy consumption. One of the methods proposed in the paper can reduce energy consumption by 3.6%, 3.6%, and 16.6% for Mecca, Riyadh, and Al-Baha, respectively. The single-objective optimisation method demonstrated that Rawshan provided sufficient UDI in four cities: Mecca, Jeddah, Riyadh, and Al-Baha. The research provided optimised values for Rawshan blind thicknesses on the front and lateral sides under different optimisation constraints. The results showed that using Rawshans in modern building architecture can reduce energy consumption and improve useful daylight illuminance.

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.

Enhancing energy efficiency while preserving sufficient daylight represents a significant challenge for residential buildings situated in hot, arid, and semi-arid climates, where cooling requirements constitute the primary component of annual energy consumption. This research introduces a parametric, multi-objective genetic algorithm (GA) workflow designed to investigate the combined impacts of window-to-wall ratio (WWR) and horizontal shading devices (HSDs) on annual energy use intensity (EUI) and useful daylight illuminance (UDI, 100–2000 lx) within a multi-story residential villa located in Al-Baha, Saudi Arabia. A baseline model was constructed in Rhino/Grasshopper and simulated utilizing Climate Studio, while Octopus was employed to produce Pareto-optimal solutions through SPEA-II and HypE across multiple generations. The optimisation targeted locations lacking daylight, with performance evaluations carried out at the home level to include extensive building trade-offs. The Pareto analysis demonstrates that the integration of controlled apertures with external shade can substantially enhance daylight access in previously poorly lit sections, with minimal alterations to the total building Energy Use Intensity (EUI). For the chosen compromise solution, the annual EUI decreases by approximately 1% compared to the baseline; however, the whole-building UDI declines, indicating that enhancing daylight in specific zones may diminish daylight availability in other areas if minimum daylight constraints are not enforced. The study illustrates a reproducible early-stage workflow and emphasizes the importance of establishing objectives and constraints that preserve daylight in habitable spaces while balancing energy efficiency and daylight performance in dwellings located in desiccated climates.