Implementation of a Scalable Aerial Crop Monitoring System for Educational Purposes (ACMS-E): The Case of Emerging Markets
The proposed study investigates the key factors influencing UAV adoption and proposes an integrated educational–operational framework to enhance implementation in agricultural practice. A case study in Sibiu County, Romania, combined survey-based empirical analysis (n = 80), strategic environmental assessment and the deployment of a demonstration aerial crop monitoring system for educational purposes (ACMS-E). We integrated the Technology Acceptance Model (TAM) and Theory of Planned Behavior (TPB) to examine adoption intentions, revealing perceived usefulness (β = 0.355, p = 0.021) and positive attitudes (β = 0.382, p = 0.005) as the strongest predictors, explaining 44.1% of variance. Based on these findings, a modular training curriculum was designed, combining theoretical instruction, flight operation exercises, remote sensing techniques, data analytics and farm-management integration. ACMS-E provides hands-on training and promotes capacity-building, bridging the gap between technological availability and real-world adoption. By linking technological capabilities with structured training, ACMS-E bridges the gap between UAV availability and effective implementation, offering a scalable model for precision agriculture. This framework provides a pathway to accelerate UAV adoption, optimize field-level monitoring and support evidence-based, resource-efficient farm management in emerging and developed agricultural contexts.
Authors
- Mircea Boșcoianu (ORCID: https://orcid.org/0000-0003-2650-7144)
- Pompilica Iagăru (ORCID: https://orcid.org/0000-0003-2275-1780)
- Sebastian Pop (ORCID: https://orcid.org/0000-0002-5296-4640)
- I. -Deaconescu Petre
- Romulus Iagăru
Institutions
- Lucian Blaga University of Sibiu (RO)
- Transylvania University of Brașov (RO)
- Henri Coanda Air Force Academy (RO)
Publication Details
- Journal
- AgriEngineering
- Published
- 2026-03-17
- DOI
- https://doi.org/10.3390/agriengineering8030115
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00