Environmental permitting is a key instrument for enabling sustainable development, but it is often characterized by long processing times, high administrative burdens, and outcome uncertainty. While prior research and government inquiries highlight weaknesses in Swedish permitting process, empirical evidence of how these challenges manifest in practice remains limited. This study investigates the permitting process through the triangulation of a scoping literature review, Swedish government reports, and an exploratory case study. The findings identify challenges related to regulatory ambiguity, institutional constraints, procedural sequencing, stakeholder participation, confidentiality, and data availability, underscoring need for a more transparent and streamlined digital permitting process.
Construction verification relies on unstructured checklists, preventing integration with autonomous systems. This paper investigates how to scalable convert legacy instructions into machine-readable data. We propose a Hybrid Inspection Pipeline using LLMs and "Balanced Retrieval-Augmented Generation" to map text into an "Inspection Triad" aligned with IFC and AEC3PO ontologies. Our system achieves 92% semantic precision while eliminating hallucinations via a deterministic fidelity loop. This provides the executable logic necessary for autonomous inspection agents and establishes a foundation for future research autonomous construction inspections.
Building information exchange in large projects remains largely file-based, although many applications require only small, task-specific subsets of data. This paper addresses the need for element-level, transactional access to building information in web-based BIM workflows, including visualization and model analysis. While direct IFC-to-web mappings are technically feasible, they often result in complex schemas and verbose queries. We present a simplified GraphQL API that enables fine-grained access to building information while abstracting IFC complexity. Through atomic geometry resources, flattened property access, and a modular schema structure, the approach improves usability, query readability, and application-oriented BIM data access.
Digital Fabrication (DFAB) proposes to increase productivity and digitalisation in Architecture, Engineering and Construction (AEC). Demonstrator projects are used to showcase novel DFAB innovations to disseminate knowledge, learning, and attract future investment to support their transfer from research to commercialisation. Currently, no unified definition of what constitutes a DFAB demonstrator in AEC exists, thus, this paper aims to provide one. This offers distinction to the phenomenon reflecting its real-world context, subsequently effecting how humans think and act on it. A definition is proposed based on analysis from literature and interviews to inform future studies on DFAB demonstrator projects in AEC.
Circular reuse of construction components, prioritized by the EU over recycling, is limited by the lack of legally reliable, element-specific information in BIM environments. This work proposes a literature-based parameter set for the reuse of reinforced concrete elements as part of a product passport. Data from legally signed inspection certificates are integrated with digital BIM representations using established ontologies (BOT, Metadata4ing, ISOProps). Information is extracted from signed PDF certificates and linked to IFC models. Feasibility is demonstrated through a case study, enabling an interoperable, auditable workflow supporting End-of-Life-to-reuse information continuity for reinforced concrete elements.
Circular construction relies on digital marketplaces to overcome supply chain fragmentation, yet manual search for reclaimed components remains a critical bottleneck. This research develops a context-aware recommendation system for reusable material matchmaking. Utilizing a multidimensional weighted ranking algorithm with hard and soft constraints, the system adaptively aligns material attributes with project requirements. Validated through expert elicitation and a design simulation user study, results demonstrate high material findability and low cognitive load. However, insufficient algorithmic transparency can induce user friction. This work establishes a foundation for role-centric matchmaking, with future research focusing on similarity score cutoffs, enhanced interpretability, and API-driven cross-platform interoperability.
This study presents the first comprehensive mapping of construction computing education in Europe, analysing 187 validated institutions across 35 countries. Using a three-tier verification methodology, we examine geographic distribution, program characteristics, and curriculum content. A sensitivity analysis estimates that current programs (~13,900 annual graduates) meet 6-49% of workforce demand depending on digitalization assumptions. Key findings include geographic concentration in Western Europe (40% in DACH and British Isles), predominance of master’s programs (58.3%), and low ISO 19650 coverage (8.6%). These findings inform educational policy and workforce planning for EU construction digitalization.
Large language models (LLMs) can automate text-intensive tasks in construction. However, preparing investigation quotations remains manual and time-consuming, with outputs varying between engineers due to non-deterministic steps like item selection and text drafting. This study proposes an LLM-assisted human-in-the-loop (HITL) workflow and evaluates several models (GPT 4.1, GPT 5, Claude Sonnet 4.5, and a fine-tuned open-source model, QwQ 32B) on 596 inquiry-quotation pairs. GPT 5 achieved the highest item-selection F1 score, while Claude 4.5 delivered comparable accuracy with the fastest processing time. This approach improves quotation efficiency and consistency, demonstrating practical benefits for construction workflows.
Successful construction management relies on interoperability, cost estimation, and scheduling. Current practices suffer from fragmented processes and data loss, due to proprietary silos and lack of automation. This research proposes a computational framework to optimize 4D and 5D BIM workflows by enriching the IFC schema. Through IfcOpenShell, the methodology provides semantic validation via IDS and collaboration via BCF, facilitating extraction of properties and quantities, scheduling, cost estimation, and resource allocation. Results indicate that an integrated OpenBIM framework using IFC as the primary source improves reliability. The contribution is a reproducible, open-source framework providing a methodology for multi-dimensional BIM management.
Construction projects, which are prone to delays and budget overruns, struggle to transform fragmented data streams into coherent intelligence. We propose a novel approach to monitoring that combines onsite data capture, agentic workflows and knowledge graph architecture to provide a foundation for evidence-based progress tracking. This approach is built on an ontology for structured schedule management that unifies concepts from domain-specific ontologies and Autodesk Construction Cloud. Autonomous AI-driven agents enable knowledge evolution by interacting with a knowledge graph. This lays the foundation for a living digital twin that adapts as new data emerges, supporting consistency checking and cross-system integration.
