Citas bibligráficas
Huamaní, J., (2021). Modelo de gestión de pavimentos en vías urbanas para mejorar el mantenimiento, basado en el tratamiento de imágenes [Tesis, Universidad Nacional de Ingeniería]. http://hdl.handle.net/20.500.14076/22397
Huamaní, J., Modelo de gestión de pavimentos en vías urbanas para mejorar el mantenimiento, basado en el tratamiento de imágenes [Tesis]. PE: Universidad Nacional de Ingeniería; 2021. http://hdl.handle.net/20.500.14076/22397
@misc{renati/711922,
title = "Modelo de gestión de pavimentos en vías urbanas para mejorar el mantenimiento, basado en el tratamiento de imágenes",
author = "Huamaní Balbín, Jesús Antonio",
publisher = "Universidad Nacional de Ingeniería",
year = "2021"
}
In this thesis, a pavement management model is proposed using UAV technology (Unmanned Aerial Vehicles). It allows obtaining georeferenced images, which when processed by means of the Pix4DiMapper program, an orthophoto and a digital surface model are obtained in 3D, which makes it possible to indirectly obtain field data, and with these determine the state of the road pavement using the PCI method (Pavement Condition Index). Likewise, to demonstrate that the proposed model is economical and saves time in collecting field data, the models were compared at the operational level based on a specific study carried out at Habich Ave. Since it is a very interesting road because it channels a high flow of vehicles from Tupac Amaru Ave. to Panamericana Norte Ave. and vice versa. With the cost saved, resources can be allocated to larger work fronts, and thus compile information on the status of all roads under the responsibility of the MML (Metropolitan Municipality of Lima). More detailed plans were also obtained than the model used by the MML, which allow a better handling and distribution of materials in the planning of maintenance works. This thesis proposes an alternative to the pavement management models that are currently applied, accelerating the obtaining of field data and the timely repair of roads by optimizing the resources of the MML.
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