TY - GEN
T1 - Precision Agriculture Drone Technology
T2 - 6th International Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2024
AU - Méndez Cam, Joseph Ramses
AU - Santos López, Félix Melchor
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
PY - 2026
Y1 - 2026
N2 - Crop pests and crop losses are constant problems in agriculture. The whole crop inspection is a time-consuming activity if it is performed manually for each plant. The implementation of an automated system would imply an integration between current technologies in precision agriculture. However, some aspects of adopting new technologies present difficulties. For example, many options regarding cameras, metrics and software are available, and choosing the right combination for each application requires research. Currently, using different cameras interchangeably is not simple. The objective of this research is to find the most used technologies for current precision agriculture with drones. In this context, a systematic review of the literature on drone precision agriculture technologies was conducted based on four research questions using the PRISMA methodology. The research method may help clarify the procedure that would be necessary to follow a project on drone design for plant health focused on multispectral and thermal cameras. This meta-analysis retrieved 5292 articles from Scopus, Taylor and Francis, Web of Science and IEEE databases. The number of articles used to answer the research questions was 75. In the end, analyzing the most frequent cameras and indices, Multispectral cameras and the Normalized Difference Vegetation Index (NDVI) were the most referenced, with 41 and 22 mentions, respectively.
AB - Crop pests and crop losses are constant problems in agriculture. The whole crop inspection is a time-consuming activity if it is performed manually for each plant. The implementation of an automated system would imply an integration between current technologies in precision agriculture. However, some aspects of adopting new technologies present difficulties. For example, many options regarding cameras, metrics and software are available, and choosing the right combination for each application requires research. Currently, using different cameras interchangeably is not simple. The objective of this research is to find the most used technologies for current precision agriculture with drones. In this context, a systematic review of the literature on drone precision agriculture technologies was conducted based on four research questions using the PRISMA methodology. The research method may help clarify the procedure that would be necessary to follow a project on drone design for plant health focused on multispectral and thermal cameras. This meta-analysis retrieved 5292 articles from Scopus, Taylor and Francis, Web of Science and IEEE databases. The number of articles used to answer the research questions was 75. In the end, analyzing the most frequent cameras and indices, Multispectral cameras and the Normalized Difference Vegetation Index (NDVI) were the most referenced, with 41 and 22 mentions, respectively.
KW - Agriculture
KW - Drone
KW - Multispectral
KW - Photogrammetry
KW - Precision
KW - Thermal
UR - https://www.scopus.com/pages/publications/105027032940
U2 - 10.1007/978-3-031-98890-5_23
DO - 10.1007/978-3-031-98890-5_23
M3 - Conference contribution
AN - SCOPUS:105027032940
SN - 9783031988899
T3 - Lecture Notes in Networks and Systems
SP - 359
EP - 379
BT - Proceedings of the International Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2024 - Volume 2
A2 - Garcia, Marcelo V.
A2 - Nuñez, Carlos
A2 - Gordón-Gallegos, Carlos
A2 - Reyes, John-Paul
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 21 October 2024 through 25 October 2024
ER -