Remote Image Capture System to Improve Aerial Supervision for Precision Irrigation in Agriculture
AbstractDue to the limitations of drones and satellites to obtain aerial images of the crops in real time, the time to flight delay, the problems caused by adverse weather conditions and other issues, the use of fixed cameras placed on the regions of interest is essential to get closer, periodic and on-demand images. Water management in agriculture is one of the most important applications of these images. Top view images of a crop can be processed for determining the percentage of green cover (PGC), and 2D images from different viewing angles can be applied for obtaining 3D models of the crops. In both cases, the obtained data can be managed for calculating several parameters such as crop evapotranspiration, water demand, detection of water deficit and indicators about solute transport of fertilizers in the plant. For this purpose, a remote image capture system has been developed for an application in lettuce crops. The system consists of several capture nodes and a local processing base station which includes image processing algorithms to obtain key features for decision-making in irrigation and harvesting strategies. Placing multiple image capture nodes allows obtaining different observation zones that are representative of the entire crop. The nodes have been designed to have autonomous power supply and wireless connection with the base station. This station carries out irrigation and harvesting decisions using the results of the processing of the images captured by the nodes and the information of other local sensors. The wireless connection is made using the ZigBee communication architecture, supported by XBee hardware. The two main benefits of this choice are its low energy consumption and the long range of the connection. View Full-Text
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Mateo-Aroca, A.; García-Mateos, G.; Ruiz-Canales, A.; Molina-García-Pardo, J.M.; Molina-Martínez, J.M. Remote Image Capture System to Improve Aerial Supervision for Precision Irrigation in Agriculture. Water 2019, 11, 255.
Mateo-Aroca A, García-Mateos G, Ruiz-Canales A, Molina-García-Pardo JM, Molina-Martínez JM. Remote Image Capture System to Improve Aerial Supervision for Precision Irrigation in Agriculture. Water. 2019; 11(2):255.Chicago/Turabian Style
Mateo-Aroca, Antonio; García-Mateos, Ginés; Ruiz-Canales, Antonio; Molina-García-Pardo, José M.; Molina-Martínez, José M. 2019. "Remote Image Capture System to Improve Aerial Supervision for Precision Irrigation in Agriculture." Water 11, no. 2: 255.
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