The digitalization of the built environment faces challenges such as interoperability, standardization, integration of legacy systems and secure data exchange. The International Data Spaces (IDS) framework, used successfully in logistics and energy, enables organizations to create value through data. This paper examines how the Vocabulary Hub, a core IDS component, addresses these challenges in the Architecture, Engineering, Construction, and Operation (AECO) sector. It outlines the setup of a domain-specific vocabulary hub and analyzes its role in semantic data exchange, suggesting that IDS is a promising approach for data integration in federated digital twin systems and structured data sharing in AECO.
Buildings significantly contribute to global energy consumption, especially in France and Europe, making their optimization crucial for addressing climate change. Integrating Building Performance Simulations (BPS) with Internet of Things (IoT) systems offers a promising solution for efficient energy management. While IoT systems enable real-time monitoring and control, they often miss complex physical phenomena like thermal dynamics. BPS fills this gap using mathematical models. However, interoperability is essential for effective collaboration. This paper presents the Web of Simulations Ontology (WoSO) to address these challenges, demonstrating its application in a pilot office building in France for the European BuildON project.
The RASE (requirements, applicability, selection and exception) approach has been developed as a means to make regulatory and other text machine-operable whilst remaining human-readable. It has delivered some substantive successes in terms of accuracy, efficiency and completeness. However, the question can be asked as to why there are four labels, and not a larger (or smaller) number. This simple question rises important questions concerning both research methodologies and about learning processes.
A Digital Building LogBook is a practical framework for capturing essential information throughout a building's life cycle. The main purpose of this ongoing research is to identify the main Building LogBook functions and to evaluate the relevance of the current recommended Building LogBook data models in those functions. The results show that the contribution percentage of data models in different functions is low due to the lack of specifying the main requirements of each function. The findings of this research clearly demonstrate that to create a functional Building LogBook data model, determining the key specifications of each function is required.
Scheduling is critical in human-robot collaboration (HRC) in construction, including work-rest scheduling and task sequencing. However, previous research often examines the two scheduling components as distinct optimization problems, neglecting their interdependence. This oversight can lead to ineffective collaboration, resulting in human fatigue and underutilized robotic capabilities. This study presents two-stage methods utilizing a modified genetic algorithm (GA) to optimize HRC scheduling. By addressing the complexities inherent in HRC environments, proposed methods aim to balance safety and productivity in construction tasks. The study also discusses the effects of the order in which scheduling components are optimized on HRC performance.
This study establishes a framework for integrating Ultra-wideband (UWB) sensor data into Building Information Modelling (BIM) systems using Autodesk Revit API (Application Programme Interface) for real-time visualization and tracking of workers. The constructed system enables dynamic monitoring of worker positions in a BIM platform, by leveraging UWB technology and Revit’s extensibility to construct a digital twin environment for construction site evaluations. The research methodology encompasses sensor data acquisition, real-time visualization, and coordinate transformation for accurate tracking. The system was experimentally tested in a controlled environment. The gathered data incorporated into a BIM model demonstrates enhanced tracking accuracy.
The AEC industry generates vast unstructured data,primarily in the form of natural languagecommunications, complicating machine-interpretableinformation retrieval. While the focus of existing researchhas been on transforming unstructured data into structuredforms, few studies address the root causes of unstructureddata generation and the complexity surrounding it.Through semi-structured interviews and thematicanalysis, this study identifies systematic, not technical,issues as primary contributors. It highlights confusion inunderstanding structured data, structured data-sharingprocesses, and BIM’s purpose and definition. The studyemphasizes the need for education on data sciencefoundations and a universally accepted understanding ofBIM.
This paper explores how model updates can be effectively facilitated for integration into models of foreign disciplines. Graph transformations are used to capture and describe the model changes introduced by one domain. These transformations are then interpreted to suggest appropriate updates for models in other disciplines. Repetitive and predictable model updates can be automated, with the necessary modifications presented to users as actionable alteration proposals. The proposed workflow reduces the burden on model authors by automating tedious yet essential tasks, allowing them to focus on solving complex design coordination challenges.
