REVIEW article
Front. Built Environ.
Sec. Building Information Modelling (BIM)
Volume 11 - 2025 | doi: 10.3389/fbuil.2025.1693644
This article is part of the Research TopicDigital Transformation in Construction: Integrating Metaverse, Digital Twin, and BIMView all 8 articles
Strategies for Bridge Maintenance Using BIM: An Analysis of Methodologies and Tools
Provisionally accepted
Emilio José Medrano-Sánchez1*
Erwin Alexander Martos2- 1Universidad San Ignacio de Loyola, Lima District, Peru
- 2Universidad Nacional de Piura, Piura, Peru
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
ABSTRACT Ageing bridge stocks and rising traffic loads in Latin America and worldwide demand cost-effective maintenance strategies. Building Information Modelling (BIM) and its convergence with digital-twin, IoT and AI techniques have shown promise, yet their adoption for bridge upkeep remains fragmentary. This review aimed to (i) synthesise current scientific evidence on BIM-based bridge maintenance, (ii) classify methodologies and tools through a domain taxonomy, and (iii) identify research gaps that hinder large-scale implementation. A PRISMA-guided systematic literature review was conducted in Scopus and Web of Science (search cut-off = 1 Feb 2024). Inclusion criteria targeted peer-reviewed, open-access studies (2020-2024) that applied BIM to the maintenance of existing bridges. Twenty-five articles met the criteria and were appraised with Mixed-Methods Appraisal Tool (MMAT 2018). Seven dominant research themes were identified, with damage visualization (7 studies) and 3-D geometric modelling (6) being the most frequent, followed by information exchange/management (4). Specifically, LiDAR and photogrammetry enabled sub-centimetre models; Convolutional Neural Networks (CNN) and You Only Look Once (YOLO) algorithms reached mean average precision up to 0.91 for crack detection. Digital-twin workflows reduced operating costs while requiring higher upfront investment. A seven-domain taxonomy and a cost–technology comparison table is proposed. Key barriers reported include IFC 4.3 interoperability, high LiDAR costs (>10% of annual budgets), limited visual-programming skills, and cybersecurity concerns in cloud-IoT integrations. BIM supports preventive, data-driven bridge maintenance and has been linked to lower operating costs in several studies; mainstream adoption requires IFC 4.3 based interoperability, targeted training, and open-standard workflows. Future research should focus on standardised performance metrics, edge-AI monitoring and blockchain-secured data exchange.
Keywords: Bridge maintenance, 3D visualization technologies, Photogrammetry and LiDAR, Real-Time Structural Monitoring, Bim
Received: 27 Aug 2025; Accepted: 09 Oct 2025.
Copyright: © 2025 Medrano-Sánchez and Martos. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Emilio José Medrano-Sánchez, emilio.medranos@epg.usil.pe
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.