Estimation of the Physical Progress of Work Using UAV and BIM in Construction Projects

• Autores: Piedra Tineo,José Luis, Cayatopa Calderon,Billy Alexis
• Formato: artículo
• Fecha de Publicación: 2024
• Institución: Universidad Nacional de Jaén
• Repositorio: UNJ-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.unj.edu.pe:20.500.14689/1052
• Enlace del recurso: http://hdl.handle.net/20.500.14689/1052; http://www.doi.org/10.28991/CEJ-2024-010-02-02
• Nivel de acceso: acceso abierto
• Materia: BIM; construction automation; construction progress; project management; UAV; https://purl.org/pe-repo/ocde/ford#2.01.01

The delay in the physical progress of construction creates additional costs, missed deadlines, and quality issues. The research aimed to estimate the physical progress of the project by using unmanned aerial vehicles (UAVs) and building information modeling (BIM). The methodology comprised capturing 848 high-resolution images of the Civil Engineering Laboratory construction site at the National University of Jaen, Cajamarca, Peru, using the Phantom 4 RTK drone. The photographs were processed using Agisoft 2.0.1 software, resulting in a point cloud. This was then imported into ReCap Pro 2023 software, which was used to assess the quality of the points. The Revit 2023 software was subsequently utilized to establish the phase parameters, linking the BIM model with the point cloud, filtering the model, and eventually exporting it to the Power BI 2023 software. The work's estimated progress utilizing the proposed methodology was 42.82%, which was not statistically significant compared to the Public Works Information System (INFOBRAS) of 43.14%. This allows for the automation of customary processes, the identification of crucial issues, and prompt decision-making. The study's originality lies in the suggestion of integrating aerial imagery with drones and BIM modeling for the real-time and precise estimation of work progression. This method provides a precise and effective substitute for traditional techniques for gauging the tangible advancement of projects.