TY  - CONF
TI  - Choosing By Advantages to select a drone for an educational surveying project
C1  - Singapore, Singapore
C3  - Proceedings of the 34th Annual Conference of the International Group for Lean Construction (IGLC 34)
SP  - 181
EP  - 193
PY  - 2026
DO  - 10.24928/2026/0244
AU  - Paucar, Anthony
AU  - Romaní, Jordan
AU  - Rivera, Coraima
AU  - Villar, Jesús
AU  - Erazo, Andrews
AU  - Braul, Andrea
AU  - Rojas, Jorge
AD  - Researcher, School of Civil Engineering, Universidad Nacional de Ingenieria, Lima, Peru, apaucare@uni.pe, orcid.org/0000-0002-5369-1584
AD  - Student Researcher, School of Civil Engineering, Universidad Nacional de Ingenieria, Lima, Peru, jordan.romani.c@uni.pe, orcid.org/0009-0007-3327-9713
AD  - Student Researcher, School of Civil Engineering, Universidad Nacional de Ingenieria, Lima, Peru, coraima.rivera.n@uni.pe, orcid.org/0009-0008-3629-0288
AD  - Student Researcher, School of Civil Engineering, Universidad Nacional de Ingenieria, Lima, Peru, jesus.villar.v@uni.pe, orcid.org/0009-0008-8461-9711
AD  - Teaching Assistant, School of Civil Engineering, Universidad Continental, Huancayo, Peru, aerazo@continental.edu.pe, orcid.org/0000-0002-5639-573X
AD  - Instructor, School of Civil Engineering, Pontificia Universidad Católica del Perú, Lima, Peru, andrea.braul@pucp.pe, orcid.org/0000-0002-1379-2591
AD  - PhD. Candidate, Lyles School of Civil and Construction Engineering, Purdue University, Indiana, USA, rojas27@purdue.edu, orcid.org/0000-0001-9372-0864
ED  - Hamzeh, Farook
ED  - Poshdar, Mani
ED  - Garcia-Lopez,, Nelly P.
AB  - Selecting drones for surveying and monitoring in construction projects is a complex multi-criteria decision-making problem, particularly in the context of Construction 4.0 and engineering education. This study applies the Choosing by Advantages (CBA) method to support the selection of a drone for photogrammetric surveying in an academic construction case study.
Four commercially available drones were evaluated using nine technical factors grouped into three categories: environmental (wind resistance, waterproof protection, operating temperature range), operational (maximum flight time, payload capacity, maximum flight speed), and data acquisition (camera resolution, frame rate, field of view). The results indicate that the drone achieving the highest total Importance of Advantages (IoA) score was the most suitable option, primarily due to the site’s environmental and climatic requirements.
Overall, the findings highlight that advantages associated with environmental and contextual factors are the most influential in selecting drones for construction management education, surpassing operational performance and data capture capabilities. This provides an evidence-based reference framework for educational stakeholders when selecting drones for adoption in construction-related teaching, research, and training.
KW  - Decision-making
KW  - Choosing by Advantages
KW  - drone
KW  - Construction 4.0.
PB  - 
T2  - Proceedings of the 34th Annual Conference of the International Group for Lean Construction (IGLC 34)
DA  - 2026/06/22
CY  - Singapore, Singapore
L1  - http://iglc.net/Papers/Details/2539/pdf
L2  - http://iglc.net/Papers/Details/2539
N1  - Export Date: 19 June 2026
DB  - IGLC.net
DP  - IGLC
LA  - English
ER  -