A Systematic Literature Review of Augmented Reality’s Development in Construction
Abstract
Augmented reality (AR) has emerged as a transformative technology, allowing users to engage with digital content overlaid on the physical world. In the construction industry, AR shows significant potential to enhance visualization, collaboration, training, and safety across the project lifecycle. This paper presents a systematic literature review (SLR) of 136 publications on the use of AR in construction published between 2019 and 2025, focusing on architectures, technologies, trends, and challenges. The review identifies the main architectures (cloud, hybrid, and local) and examines how AR is combined with Building Information Modeling (BIM) systems, digital twins, the Internet of Things (IoT), and Unmanned Aerial Vehicles (UAVs). Key application trends are identified and discussed, including on-site visualization, inspection and monitoring, immersive training, hazard detection, and remote collaboration. Challenges and constraints to the adoption of AR in construction are highlighted and examined such as hardware limitations, usability and ergonomics issues, interoperability with existing systems, high costs, and resistance to organizational change. By systematizing existing approaches and mapping both opportunities and barriers, this review provides a comprehensive reference for researchers, practitioners, and policy makers aiming to accelerate AR adoption in the construction sector.
Read the paper
Related studies
- Knowledge Management Perspective of Generative Artificial Intelligence
- Navigating Generative Artificial Intelligence Promises and Perils for Knowledge and Creative Work
- Characterizing the evolving research on enterprise content management
- Large language models and multimodal foundation models for precision oncology
- From Generative AI to Extended Reality: Multidisciplinary Perspectives on the Challenges, Opportunities, and Future of Educational Computing
- Generative Artificial Intelligence: A New Engine for Advancing Environmental Science and Engineering
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.