Gemelos digitales para la supervisión y el mantenimiento de infraestructuras viales: Revisión sistemática
Digital twins for road infrastructure monitoring and maintenance: A systematic reviewContenido principal del artículo
Los Gemelos Digitales (DT) emergen como una solución tecnológica prometedora para la gestión eficiente y el mantenimiento proactivo de la infraestructura vial. El objetivo del estudio es analizar la literatura científica sobre la aplicación de Gemelos Digitales para el monitoreo y mantenimiento de la infraestructura vial. El enfoque del estudio es cualitativo, bajo una revisión sistemática orientada en la metodología PRISMA. Las bases de datos utilizadas Scopus, Web of Science y Google Scholar. Se analizan 21 estudios publicados del periodo 2020 hasta 2025. Los hallazgos indican un uso predominante de BIM, IoT e Inteligencia Artificial para el monitoreo de condición y detección de daños. Aunque se reportan beneficios en eficiencia y precisión, persisten desafíos en interoperabilidad de datos, costos de implementación y estandarización. Se concluye que, si bien los DT poseen un gran potencial transformador, se requiere mayor investigación en validaciones a gran escala y desarrollo de soluciones estandarizadas para su adopción generalizada.
Digital Twins (DTs) are emerging as a promising technological solution for the efficient management and proactive maintenance of road infrastructure. The objective of this study is to analyze the scientific literature on the application of Digital Twins for road infrastructure monitoring and maintenance. The study's approach is qualitative, based on a systematic review guided by the PRISMA methodology. The databases used are Scopus, Web of Science, and Google Scholar. Twenty-one published studies from 2020 to 2025 are analyzed. The findings indicate a predominant use of BIM, IoT, and Artificial Intelligence for condition monitoring and damage detection. Although benefits in efficiency and accuracy are reported, challenges persist in data interoperability, implementation costs, and standardization. It is concluded that, while DTs have great transformative potential, further research is required in large-scale validations and the development of standardized solutions for their widespread adoption.
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Referencias
Banco de Desarrollo de América Latina CAF. (2020). Infraestructura en el desarrollo de América Latina: Tendencias, brechas y oportunidades. https://scioteca.caf.com/handle/123456789/1634
Buuveibaatar, M., Brilakis, I., Peck, M., Economides, G., y Lee, W. (2025). A Conceptual Framework for Planning Road Digital Twins. Buildings, 15(3), 316. https://doi.org/10.3390/buildings15030316
Buuveibaatar, M., Shin, S., y Lee, W. (2025). Digital twin framework for road infrastructure management. Applied Sciences, 15(10), 5765. https://doi.org/10.3390/app15105765
CEPAL (Comisión Económica para América Latina y el Caribe). (2004). La infraestructura en el desarrollo de América Latina. https://repositorio.cepal.org/bitstream/handle/11362/6376/1/S2004015_es.pdf
Chang, X., Zhang, R., Mao, J., y Fu, Y. (2024). Digital Twins in Transportation Infrastructure: An Investigation of the Key Enabling Technologies, Applications, and Challenges. IEEE Transactions on Intelligent Transportation Systems, Early Access. https://doi.org/10.1109/TITS.2024.3401716
Consilvio, A., Hernández, J. S., Chen, W., Brilakis, I., Bartoccini, L., Di Gennaro, F., y van Welie, M. (2023). Towards a digital twin-based intelligent decision support for road maintenance. Transportation Research Procedia, 69, 791-798. https://doi.org/10.1016/j.trpro.2022.12.085
Evans, S., Saviano, C., Quemaduras, A., y Cooper, C. (2020). Digital Twins for the Built Environment. The IET (Institution of Engineering and Technology). https://www.theiet.org/impact-society/sectors/built-environment/built-environment-news/2019-news/digital-twins-for-the-built-environment
Fu, H., Zhao, T., Chen, Y., Yao, Y., y Leng, J. (2023). Framework and operation of digital twin smart freeway. IET Intelligent Transport Systems, 17(3), 620–633. https://doi.org/10.1049/itr2.12288
Heise, I., Esser, S., y Borrmann, A. (2024). Towards a comprehensive digital twin of a road infrastructure system - Requirements analysis and system architecture. ResearchGate Publication. https://www.researchgate.net/publication/382181786_Towards_a_comprehensive_digital_twin_of_a_road_infrastructure_system_-_Requirements_analysis_and_System_architecture
Jiang, F., Ma, L., Broyd, T., Chen, W., y Luo, H. (2022). Building digital twins of existing highways using map data based on engineering expertise. Automation in Construction, 134, 104081. https://doi.org/10.1016/j.autcon.2021.104081
Meza, S., Mauko Pranjić, A., Vezok, R., Osmokrović, I., y Lenart, S. (2021). Digital twins and road construction using secondary raw materials. Journal of Advanced Transportation, 2021, Article 6689189. https://doi.org/10.1155/2021/6689189
Ministerio de Economía y Finanzas del Perú. (2019). Plan Nacional de Infraestructura para la Competitividad. https://repositorio.minedu.gob.pe/handle/20.500.12799/6700
Ministerio de Economía y Finanzas del Perú. (2021). Nota técnica para la identificación y estimación de los costos de mantenimiento de inversiones. https://www.mef.gob.pe/contenidos/inv_publica/docs/capacitaciones/Capacitacion_2022_08_17_1.pdf
Ministerio de Economía y Finanzas del Perú. (2019). Informe Económico: Indicadores de calidad de infraestructura. (Referencia secundaria en: ComexPerú, 2025). https://www.mef.gob.pe/es/ComexPerú, 2025.
Munasinghe, T., y Pasindu, H. R. (2021). Sensing and mapping for better roads: initial plan for using federated learning and implementing a digital twin to identify the road conditions in a developing country-Sri Lanka. arXiv:2107.14551 [cs.CY]. https://arxiv.org/abs/2107.14551
Oditallah, M., Alam, M., Ekambaram, P., y Ranjha, S. (2025). Review and Insights Toward Cognitive Digital Twins in Pavement Assets for Construction 5.0. Infrastructures, 10(3), 64. https://doi.org/10.3390/infrastructures10030064
Oreto, C., Massotti, L., Biancardo, S. A., Veropalumbo, R., Viscione, N., y Russo, F. (2021). BIM-based pavement management tool for scheduling urban road maintenance. Infrastructures, 6(11), 148. https://doi.org/10.3390/infrastructures6110148
Paterson, D., y Rossigny, P. (2022). Road Asset Management for Developing Countries.
https://openknowledge.worldbank.org/entities/publication/7d1b3f8c-7a7c-5e7c-bc6f-9a5e6e8b5e2c
Pregnolato, M., Gunner, S., Voyagaki, E., De Risi, R., Carhart, N., Gavriel, G., Tully, P., Tryfonas, T., Macdonald, J., y Taylor, C. (2022). Towards Civil Engineering 4.0: Concept, workflow and application of digital twins for existing infrastructure. Automation in Construction, 141, 104421. https://doi.org/10.1016/j.autcon.2022.104421
Rozas, D., y Sánchez, R. (2004). Infraestructura y desarrollo en América Latina. https://repositorio.cepal.org/bitstream/handle/11362/6376/1/S2004015_es.pdf
Sanfilippo, F., Thorstensen, R. T., Jha, A., Jiang, Z., y Robbersmyr, K. G. (2022). A Perspective Review on Digital Twins for Roads, Bridges, and Civil Infrastructures. In 2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) (pp. 1-6). IEEE. https://doi.org/10.1109/ICECCME55909.2022.9988693
Sark, M., y Sadhu, A. (2024). Recent progress and future outlook of digital twins in structural health monitoring of civil infrastructure. Smart Materials and Structures, 33(3), 033001. https://doi.org/10.1088/1361-665X/ad2bd7
Sauer, P. C., y Seuring, S. (2023). How to conduct systematic literature reviews in management research: a guide in 6 steps and 14 decisions. Review of Managerial Science, 17(5), 1899–1933. https://doi.org/10.1007/s11846-023-00668-3
Scolamiero, V., y Boccardo, P. (2025). Mobile Mapping System for Urban Infrastructure Monitoring: Digital Twin Implementation in Road Asset Management. Land, 14(3), [Número de artículo - si estuviera disponible, se añadiría. Se asume que el PDF era un pre-print o versión aceptada]. https://iris.uniroma1.it/retrieve/1e26ed99-ffe2-4d6e-b670-b1473ad3083b/Scolamiero_Mobile-mapping-system_2025.pdf
Sierra, C., Paul, S., Rahman, M. A., y Kulkarni, A. (2022). Development of a cognitive digital twin for pavement infrastructure health monitoring. Infrastructures, 7(8), 113. https://doi.org/10.3390/infrastructures7080113
Sun, Z., Jayasinghe, S., Sidiq, A., Shahrivar, F., Mahmoodian, M., y Setunge, S. (2024). Approach Towards the Development of Digital Twin for Structural Health Monitoring of Civil Infrastructure: A Comprehensive Review. Sensors, 24(1), 59. https://doi.org/10.3390/s24010059
Talaghat, M. A., Golroo, A., Kharbouch, A., Rasti, M., Heikkilä, R., y Jurva, R. (2024). Digital twin technology for road pavement. Automation in Construction, 168, 105826. https://doi.org/10.1016/j.autcon.2024.105826
Wu, D., Zheng, A., Yu, W., Cao, H., Ling, Q., Liu, J., y Zhou, D. (2025). Digital Twin Technology in Transportation Infrastructure: A Comprehensive Survey of Current Applications, Challenges, and Future Directions. Applied Sciences, 15(4), 1911. https://doi.org/10.3390/app15041911
Yan, B., Yang, F., Qiu, S., Wang, J., Cai, B., Wang, S., Li, X., y Hu, W. (2023). Digital twin in transportation infrastructure management: a systematic review. Intelligent Transportation Infrastructure, 2, liad024. https://doi.org/10.1093/iti/liad024
Yu, D., y He, Z. (2022). Digital twin-driven intelligence disaster prevention and mitigation for infrastructure: advances, challenges, and opportunities. Natural Hazards, 112(1), 1–36. https://doi.org/10.1007/s11069-021-05190-x
Yu, G., Zhang, S., Hu, M., y Wang, Y. K. (2020). Prediction of highway tunnel pavement performance based on digital twin and multiple time series stacking. Advances in Civil Engineering, 2020, Article 8824135. https://doi.org/10.1155/2020/8824135
Zheng, L., Meyendorf, N., y Mrad, N. (2018). The role of data fusion in predictive maintenance using digital twins. AIP Conference Proceedings, 1949(1), 020023. https://doi.org/10.1063/1.5031520
Zhengji, L., Xu, X., Jiacheng, X., Yuxiao, F., Wentao, W., Gang, C., Liqiang, Z., y Tianyang, W. (2024). A Efficient and Robust Framework for Pavement Damage Detection. arXiv:2405.17905 [cs.CV]. https://arxiv.org/abs/2405.17905
Zhu, J., Zhong, J., Ma, T., Huang, X., Zhang, W., y Zhou, Y. (2022). Pavement distress detection using convolutional neural networks with images captured via UAV. Automation in Construction, 133, 103991. https://doi.org/10.1016/j.autcon.2021.103991
Zhu, S., Peng, B., Li, D., Bai, Y., Liu, X., y Li, Y. (2024). Methods for Addressing Pavement Defects Based on Digital Twin Technology--A Case Study of Snow and Water Accumulation on Road Surface. In E3S Web of Conferences (Vol. 512, p. 04015). EDP Sciences. https://doi.org/10.1051/e3sconf/202451204015