Cost estimation for tendering is one of the leading causes of legal disputes in the architecture, engineering, construction, and facilities management (AEC/FM) industry. To date, there are no standardized procedures for verifying cost estimation accuracy. The association between cost data and geometric model objects is currently done manually, leading to time losses and inaccuracies in cost estimates. This study defines a new architecture for cost items within the Industry Foundation Classes (IFC) data model to ensure structured cost data, which is currently expressed in unstructured natural language. It encompasses the definition of a cost domain in IFC, potential relationships it may have with an IFC geometric information model, and the validation of these relationships through semi-automated verification procedures of structured data (geometric-cost). A specific case study, focused on a structural IFC model, is examined to assess current and future applications. Additionally, rules for BIM information requirements will be defined through the Information Delivery Specification (IDS) to ensure clear understanding for both humans and computers. This will specify which data must be included in the geometric model to ensure validation and verification of the uniqueness of associated cost data. The results demonstrate the feasibility of defining structured cost elements in IFC and verifying their association with geometric data to ensure coherence and uniqueness in cost estimation.

Internal hospital logistics are inherently complex, characterized by the critical need to move essential materials with high efficiency, precision, and safety. The adoption of automated guided vehicles (AGVs) is essential for automating these flows, but designing and optimizing their routes represents a significant challenge. This study presents a methodology for analyzing and optimizing AGV paths within healthcare facilities, effectively managing three-dimensional spatial complexity. The methodology leverages BIM and the open IFC standard to obtain an accurate geometric and semantic representation of the building. These data are then converted into a graph model using graph theory. Pathfinding algorithms, such as A*, are applied to this graph to calculate and optimize AGV trajectories, considering operational and collision constraints. The approach provides distance-optimized AGV paths. The integration of BIM, IFC, and graph theory proves to be an effective tool for logistical planning, simulation, and proactive management of AGVs in multi-level environments. This research contributes to the digital transformation of the construction sector by demonstrating how the integration of open standards and advanced algorithms can optimize the operational performance of complex buildings. By bridging the gap between architectural modeling and robotic logistics, the proposed approach supports the development of “smart buildings” and promotes more sustainable and technologically advanced management of healthcare facilities.

Interoperability between digital models in the manufacturing and AEC domains is a critical issue in the building design of complex systems. Despite the adoption of well-established standards such as STEP (STandard for the Exchange of Product data, ISO 10303-21) for the industrial domain and IFC (Industry Foundation Classes, ISO 16739-1) for the construction domain, communication between these domains is still limited due to differences in conceptual models, levels of detail, and application purposes. Existing solutions for conversion between these formats are few, often proprietary, and not always suitable to ensure full semantic integration in BIM (Building Information Modeling) flows. This study proposes a methodological framework for structured conversion from STEP to IFC-SPF (STEP Physical File), based on information and geometric simplification and data enrichment. The process includes the elimination of irrelevant components, simplification of geometries, merging assemblies, and integration of data useful to the building context. The experimental implementation, carried out using the Bonsai extension for Blender, demonstrates a substantial reduction in geometric complexity and computational load, while maintaining data consistency required for integration into BIM processes. This approach emerges as a scalable, affordable, and sustainable solution for interoperability between industrial and civil models, even in professional environments lacking advanced software development skills.

Building Energy Modelling (BEM) for existing buildings is constrained by the lack of reliable as-built Building Information Models (BIMs) and persistent BIM-to-BEM interoperability problems. This study proposes a semantic scan-to-Industry Foundation Classes (IFC) workflow that converts mobile indoor scans into a simplified IFC model for BEM preprocessing. Apple RoomPlan captures room-scale building elements, which are exported as JSON and converted into IFC 4×3 ADD2 using a Python-based converter. To address partial scans, the workflow generates closed analytical volumes, inferred walls and ceiling slabs, and metadata distinguishing measured from reconstructed geometry. It then automatically generates IfcSpace entities and IfcRelSpaceBoundary2ndLevel relationships. The workflow was evaluated using a historic university building. For the selected case-study area, processing from mobile scanning to initial VICUS Buildings import required 21 min, excluding subsequent manual verification of boundary conditions and assignment of thermophysical properties. Under identical construction stratigraphies and usage profiles, the scan-derived model produced a total heating-season demand 5.8% higher than the Revit reference model. These results indicate that partial semantic indoor scans can support the rapid preparation of structured IFC models for preliminary BEM applications.

In the architecture, engineering, construction, and facilities management (AEC/FM) industry methodologies are needed to ensure the interoperability of data and effective management of information from different sources. Integration of the cost domain and cost estimation within the Building Information Model (BIM) in the AEC/FM sector is still an unresolved problem and one of the most critical tasks due to the lack of a standardised cost domain, especially in the tendering phase. To ensure interoperability between cost data and geometric data, this research aims to address this gap by analyzing methods of converting cost data into Linked Building Data, thereby defining a cost domain in the Semantic Web, by collecting them into a graph database. This allows for structuring a cost domain, translating an IFC based structure previously developed by the research group, visualizing it using a graph system, and connecting it to the BIM geometric domain. Furthermore, it is possible to extend the cost ontology previously identified in the IFC model and facilitate the queries and analysis of cost data currently fragmented and based on unstructured data. The results show how Semantic Web technology can be used to improve data interoperability, develop a cost ontology, and join both cost data and BIM models

Project control in cost estimation, time scheduling, and resource accounting remains challenging, particularly when using the open-source Industry Foundation Classes (IFCs) format. This study aims to define the state of the art in integrating these three domains. A systematic literature review was conducted, using a bibliometric analysis to map and interpret scientific knowledge and research trajectories, and an inductive analysis for a detailed examination of relevant studies. The analysis highlights a lack of clarity in applying the IFC standard across project control domains, as current practices often rely on non-standardized procedures, including incorrect use of classes or properties, creation of unneeded user-defined PropertySets and properties, or reliance on proprietary software. Integration of cost, time, and resource management remains limited, and proposed technological solutions generally require coding skills that typical professionals do not possess. Additional challenges include fragmented data across multiple databases, manual assignment of time, cost, and resource information, and limited collaboration, all of which are time-consuming and error-prone. There is a critical need for clearer guidelines on IFC usage to enable standardized procedures and facilitate the development of IFC-based tools. Automating these labor-intensive tasks could improve efficiency, reduce errors, and support broader adoption of integrated project control practices.