Abstract
This work presents an unmanned aerial vehicle management platform encompassed in the concept of smart farming. Automates inspections of different \(\text {crops}\) and monitors the status of the plantation is done by IoT, analyzing an area on an online map that provides air and weather restrictions. Intelligent route management algorithms are employed to generate the optimal inspection route and waypoints, maximizing the multispectral images capture. These multispectral images can be subsequently processed according to algorithms based on phytosanitary index formulas and regressions obtained with artificial neural networks. Reports are generated with analysis of the results by this approach, for example: optimal collection time, water stress, maturity index, etc.
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Acknowledgements
The work reported herewith has been financially by the Dirección General de Universidades, Investigación e Innovación of Castilla-La Mancha, under Research Grant (Ref.: SBPLY/19/180501/000102).
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Gómez Muñoz, C.Q., Paredes Alvarez, C., Garcia Marquez, F.P. (2021). Smart Farming: Intelligent Management Approach for Crop Inspection and Evaluation Employing Unmanned Aerial Vehicles. In: Xu, J., Duca, G., Ahmed, S., García Márquez, F., Hajiyev, A. (eds) Proceedings of the Fourteenth International Conference on Management Science and Engineering Management. ICMSEM 2020. Advances in Intelligent Systems and Computing, vol 1191. Springer, Cham. https://doi.org/10.1007/978-3-030-49889-4_11
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