APLICACIÓN DE SOFTWARE PARA LA GESTIÓN DEL PROCESAMIENTO DE IMÁGENES AÉREAS DE PLANTÍOS (SOFTWARE APPLICATION FOR THE MANAGEMENT OF PROCESSING AERIAL IMAGES OF CROPS)
Resumen
La agricultura de precisión consiste en la automatización de eventos agrícolas utilizando tecnologías de Internet de las cosas (IoT) para la toma de decisiones basadas en datos, en forma automática e inteligente, lo que lleva a una producción mejorada con menos esfuerzos humanos. En este sentido, la recuperación de datos reales sobre las condiciones de los plantíos mediante el procesamiento de imágenes aéreas de alta resolución de los cultivos para extraer datos para la toma de decisiones futuras. En este artículo se propone una aplicación de software para dispositivos móviles con sistema operativo Android para la gestión del procesamiento de imágenes y la detección de coloración de plantas en cultivo extensos. Las imágenes aéreas de cultivos se capturan e identifican (localización) mediante un vehículo aéreo no tripulado. Posteriormente, la imagen es procesada y resalta los colores identificados en los cultivos de la parcela muestreada. Lo anterior, permite la toma de decisiones basada en datos, ubicando mediante la aplicación de software el lugar donde se encuentren grupos de plantas dañadas o afectadas en la parcela.
Palabras Clave: procesamiento de imagen, aplicación de software, UAV, IoT, agricultura de precisión.
Abstract
Precision agriculture is the automation of agricultural events using Internet of Things (IoT) technologies for automatic and intelligent data-driven decision-making, leading to improved production with less human effort. In this sense, the recovery of real data on the conditions of the plantations through the processing of high-resolution aerial images of the crops to extract data for future decision-making. This article proposes a software application for mobile devices with an Android operating system for the management of image processing and the detection of coloration of plants in large crops. Crop aerial images are captured and identified (located) by an unmanned aerial vehicle. Subsequently, the image is processed and highlights the colors recognized in the crops of the sampled field. This allows decision-making based on data, locating through the software application where groups of damaged or affected plants are on the field.
Keywords: image processing, mobile application, UAV, IoT, precision agriculture.
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Alvarado Moreno J. D., Garcia L.C., Hernández W.C. and Barrera Obando A.M., "Embedded Systems for Internet of Things (IoT) Applications: A Review Study," in 2018 Congreso Internacional de Innovación y Tendencias en Ingeniería (CONIITI), Bogota, Colombia, 2018, pp. 1-6, doi: 10.1109/CONIITI.2018.8587092.
Cattani, C.E.V., Garcia, M.R., Mercante, E., Johann, J.A., Correa, M.M., Oldoci, L.V., 2017, Spectral-temporal characterization of wheat cultivars through NDVI obtained by terrestrial sensors, Revista Brasileira de Engenharia Agricola e Ambiental, Vol. 21(11), doi: 10.1590/1807-1929/agriambi.v21n11p769-773.
Daponte P., De Vito L., Glielmo L., Lannelli L., Liuzza D., Picariello F. and Silano G., “A review on the use of drones for precision agriculture,” in IOP Conference Series: Earth and Environmental Science, Volume 275, 1st Workshop on Metrology for Agriculture and Forestry (METROAGRIFOR) 1–2 October 2018, Ancona, Italy. DOI 10.1088/1755-1315/275/1/012022.
Kizilgeci, F., Yildirim, M., Islam, M.S., Ratnasekera, D., Iqbal, M.A., Sabagh, A.E., 2021, Normalized Difference Vegetation Index and Chlorophyll Content for Precision Nitrogen Management in Durum Wheat Cultivars under Semi-Arid Conditions, Sustainability, Vol. 13:3725, doi: 10.3390/ su13073725.
Nixon M.S. and Aguado A.S., “Feature Extraction and Image Processing for Computer Vision,” Academic Press, 4th. Edition. 2020. DOI: https://doi.org/10.1016/C2017-0-02153-5.
Patrício D.I. and Rieder R., “Computer vision and artificial intelligence in precision agriculture for grain crops: A systematic review.” Computers and Electronics in Agriculture, 153, 2018, pp. 69-81. https://doi.org/10.1016/j.compag.2018.08.001.
Paolanti M. and Frontoni E., “Multidisciplinary Pattern Recognition applications: A review,” Computer Science Review, 37 (100276), 2020, https://doi.org/10.1016/j.cosrev.2020.100276.
Petrou Maria M. P., Sei-ichiro Kamata. Image Processing: Dealing with Texture, 2nd Edition. 2021. Wiley.
Poma J. M. C., De la Cruz Dominguez E. Y., Armas-Aguirre J. and Gutierrez González L., "Extended Model for the Early Skin Cancer Detection Using Image Processing," 2020 15th Iberian Conference on Information Systems and Technologies (CISTI), Seville, Spain, 2020, pp. 1-6, doi: 10.23919/CISTI49556.2020.9140952.
Samangouei P., Patel V. M. and Chellappa R., “Facial attributes for active authentication on mobile devices,” Image and Vision Computing, 58, pp. 181-192, 2017. https://doi.org/10.1016/j.imavis.2016.05.004.
Shafi U., Mumtaz R., García-Nieto J., Hassan S. A., Zaidi S. A. R., and Iqbal N., “Precision Agriculture Techniques and Practices: From Considerations to Applications,” Sensors, vol. 19, no. 17, p. 3796, Sep. 2019, doi: 10.3390/s19173796.
Sharma A., Jain A., Gupta P. and Chowdary V., "Machine Learning Applications for Precision Agriculture: A Comprehensive Review," in IEEE Access, vol. 9, pp. 4843-4873, 2021, doi: 10.1109/ACCESS.2020.3048415.
Tsouros D. C., Bibi S., and Sarigiannidis P. G., “A Review on UAV-Based Applications for Precision Agriculture,” Information, vol. 10, no. 11, p. 349, Nov. 2019, doi: 10.3390/info10110349.
Zhang X. -Y., Liu C. -L. and Suen C. Y., "Towards Robust Pattern Recognition: A Review," in Proceedings of the IEEE, vol. 108, no. 6, pp. 894-922, June 2020, doi: 10.1109/JPROC.2020.2989782.
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