... 06 2026 © 2026 Emerald Publishing Limited 2026 Emerald Publishing Limited Licensed re-use rights only aerodynamic force aerodynamic torque artificial intelligence bogie data high-velocity locomotive neural networks tunnel N–S Navier–Stokes k − ϵ turbulence...

.... This precise gap motivates our integrated AI–IoT–GIS prototype and the experimental design reported below. Rather than constituting a case-specific engineering integration, this formulation reframes urban flood resilience as a constrained inference-and-decision problem under structural data sparsity...

... prediction model was 2.3%, the average relative error of the traditional SVM model in the same data set was 6.8% and that of the chaotic time-series model was 4.1%. Compared with the prediction ability of the traditional models currently used, the prediction ability of the energy consumption prediction model...

...Jiming Hu, MSc; Xiaoyan Han, PhD In order to solve the problem of excessive burden of electricity and energy consumption in urban landscape buildings clusters, the study combined data mining algorithms to establish a prediction model for energy-saving renovation of urban landscape building clusters...

... and control to facility managers by automating all levels of information access (from granular data to defined key performance indicators and reports) and actuation. This paper proposes a low-latency data integration method that supports actuation and decision making in facility management, including...

..., PhD; Peter Oliver, PhD, FBCS; Aruna Sivakumar, PhD; Theodoros Tryfonas, PhD, FRSA; Liz Varga, PhD, FCABE, FAcSS, FHEA Research into the engineering of infrastructure systems is increasingly data intensive. Researchers build computational models to explore scenarios such as investigating the merits...

... building operation data in real time to identify energy wastes as well as suitable energy conservation measures that shall help in saving energy. One main challenge is to provide a highly scalable solution that can be easily applied in a wider range of buildings, thus enabling resource saving at a large...

... unsupervised machine learning algorithms and smartphone sensors. The evaluation of roadways utilising complex contemporary data sets is currently conducted periodically because of the high cost of collection methods. For this purpose, the study presents a data-driven framework on the use of a vehicle...

..., (b) the need for a small number of top-level ontologies and translation mechanisms between them and (c) clarity on the role of standards and information systems in the adaptability and quality of data sets using ontologies. A gap is also identified in the extent that ontologies can support...

... and asset information specification tools to improve information transfer between building designers, contractors and facility/asset managers. The Infrastructure Asset Data project focuses on the use of metadata standards to federate and analyse data on three waters pipe networks managed by different...

...-year return period by using the Gumbel probability distribution. However, recently reported cyclones were extreme wind events that already exceeded the specified value in the code. The Gumbel distribution (type I) is applied in the present study by using the method of moments on the long-term wind data...

...Aaron Johnson; James Heaton; Steven Yule; Sam Luke; David Pocock; Ajith Kumar Parlikad; Jennifer Schooling The right data to the right people at the right time are a crucial component to developing an effective digital twin (DT). A challenge in the industry is that existing legacy data systems have...

...Cathal Hoare, BSc; Sergio Pinheiro, PhD; Shushan Hu, PhD; James O’Donnell, PhD The evolution of information and communication technology in the construction domain has yielded a variety of heterogeneous data sources. While bespoke approaches have been developed to explore data merging for a variety...