Uso De Drones Para El Analisis De Imágenes Multiespectrales en Agricultura De Precisión

En los últimos años, la proliferación y fácil acceso a los vehículos aéreos no tripulados (uav) ha causado un gran número de incidentes en el mundo. Los gobiernos han aunado esfuerzos para regular y controlar la operación de estos sistemas, al impulsar la creación de soluciones que permitan detectar y mitigar posibles ataques mediante estas plataformas. En el presente artículo se describe el proceso de diseño e implementación de un prototipo de inhibición de uav para las bandas gps (L1 y L2), WiFi 2.4 GHz y WiFi 5.8 GHz. Los resultados de las pruebas realizadas mostraron un alcance de inhibición de 150m con una potencia de transmisión por banda menor a 25 dBm.

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Coffee Crops Analysis Using UAVs Equipped with Multispectral Cameras

Arteaga-López,

Delgado-Calvache,

Casanova

et al. 2022

Rev. Fac. Ing.

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The use of Unmanned Aerial Vehicles (UAVs) equipped with spectral cameras has increased in recent years, especially in the agricultural sector, because it allows farmers and researchers to analyze the state of a crop, i.e., health, nutrients, growth, epidemics, among other parameters. In Colombia, the coffee production sector faces several challenges, such as the need to increase the productivity, the yield, and the quality of coffee. This work estimated the health status of a Castilla variety crop located in San Joaquín, Tambo, Cauca to support the decision-making of coffee growers. For this, chlorophyll data were measured in the field with the CCM-200 plus device, multispectral images were captured with the MAPIR SURVEY 3 camera airborne on a SOLO 3DR UAV, and synthetic data were generated to increase the data set. Six vegetation indices were set, which—together with the chlorophyll values—were modeled through the implementation of simple and multiple linear regressions, decision trees, vector machines, random forests, and k-nearest neighbors. The model with the best performance and the lowest mean square error was disorder with the support vector machine. Likewise, the best performance indices in the models were CVI, GNDVI, and GCI, which are widely used in agriculture to estimate the chlorophyll of plants.

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Uso De Drones Para El Analisis De Imágenes Multiespectrales en Agricultura De Precisión

Cited by 5 publications

References 1 publication

Cover Missions Planning for Unmanned Aerial Vehicles

Cover Missions Planning for Unmanned Aerial Vehicles

Diseño e implementación de un prototipo inhibidor de un vehículo aéreo no tripulado (UAV)

Coffee Crops Analysis Using UAVs Equipped with Multispectral Cameras

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