Use of Drone Photogrammetry as An Innovative, Competency-Based Architecture Teaching Process

Author:

Rábago Jordi1ORCID,Portuguez-Castro May2ORCID

Affiliation:

1. School of Architecture, Art, and Design, Tecnologico de Monterrey, Leon 37190, Mexico

2. Institute for the Future of Education, Tecnologico de Monterrey, Monterrey 64849, Mexico

Abstract

The use of drones is becoming increasingly popular in various fields. In the case of education, initiatives have emerged in which they are included as tools to develop student’s knowledge, and their use is becoming more frequent. This research aims to present a case study in which students used drones in an architecture course at a higher education institution in Mexico. It sought to develop transversal competencies in students, such as digital transformation and cutting-edge technologies by studying spaces using photogrammetry with drones. The results showed that students increased their motivation and were able to perform a more detailed analysis of the architectural space in which they conducted the study. Additionally, they were able to capture and analyze information from architectural study processes more quickly. Aerial photogrammetry is a geospatial data collection method that offers several advantages over other methods. These advantages include higher resolution, wide coverage, flexibility, lower costs, and increased safety. Aerial photogrammetry can capture high-resolution images of large areas of land in a single flight, making it an efficient and adaptable tool for a variety of applications and environments. Additionally, it can be more economical and safer than other methods, as it avoids ground contact and reduces risks to personnel and equipment. This study is considered attractive, as it presents an example of the implementation of emerging technologies in architectural education.

Funder

Novus

Publisher

MDPI AG

Subject

Artificial Intelligence,Computer Science Applications,Aerospace Engineering,Information Systems,Control and Systems Engineering

Reference30 articles.

1. Li, J., Kacimi, R., Liu, T., Ma, X., and Dhaou, R. (2022). Non-Terrestrial Networks-Enabled Internet of Things: UAV-Centric Architectures, Applications, and Open Issues. Drones, 6.

2. Cavoukian, A. (2012). Privacy and Drones: Unmanned Aerial Vehicles, Information and Privacy Commissioner of Ontario.

3. Fina, L., Smith, D.S., Carnahan, J., and Sevil, H.E. (2022). Entropy-Based Distributed Behavior Modeling for Multi-Agent UAVs. Drones, 6.

4. A Review of Photogrammetry and Photorealistic 3D Models in Education from a Psychological Perspective;Nebel;Front. Educ.,2020

5. The Accuracy of Automatic Photogrammetric Techniques on Ultra-Light Uav Imagery. Int. Arch. Photogramm;Strecha;Remote Sens. Spat. Inf. Sci.,2011

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