Virtual worlds in AECO operations: Towards a human-centric framework
The AECO industry faces persistent challenges, including fragmentation, inefficiencies, and limited human-centric integration in digital workflows. While BIM and Digital Twins (DTs) have advanced digitalization, they often lack the immersive, multi-user, and interactive environments crucial for Industry 5.0 and Construction 5.0. This paper presents a comprehensive review of Virtual Worlds (VWs) and their potential for the AECO sector. Based on this review, a human-centric methodological and technological framework is proposed, structured across four synergistic layers: Data & Context; Processing & Simulation; Interaction & Visualization; and Integration & Connectivity. This framework integrates Extended Reality (XR), Artificial Intelligence (AI), and Gaming Technology with existing BIM and DTs data. Its applicability is conceptually illustrated through five research prototypes, demonstrating its potential to guide advancements in collaboration, simulation, visualization, and human-machine interaction in AECO. This work contributes a structured vision and roadmap for fostering more efficient, collaborative, and human-augmented digital practices. • Comprehensive review on Human-centric Virtual Worlds (VWs) for AECO Operations. • Presents a 4-layer VW framework integrating XR, AI, Gaming Tech, BIM, and DTs. • Fosters immersive, multi-user collaboration beyond traditional BIM/DT limitations. • Illustrated via five research prototypes for training, design, and inspection. • Provides a roadmap for VW adoption in AECO aligned with Construction 5.0.
Authors
- P. Mathias (ORCID: https://orcid.org/0000-0001-7748-0178)
- Marely del Rosario Cruz Felipe (ORCID: https://orcid.org/0000-0003-1937-1568)
- Morales Maridueña Vicente Javier
Institutions
- Pontificia Universidad Católica de Valparaíso (CL)
- International Center for Numerical Methods in Engineering (ES)
- Universitat Politècnica de Catalunya (ES)
Publication Details
- Journal
- Automation in Construction
- Published
- 2025-09-10
- DOI
- https://doi.org/10.1016/j.autcon.2025.106529
- Citations
- 1
- Primary Topic
- Human-Automation Interaction and Safety
- Type
- article
- Field-Weighted Citation Impact
- 2.44