Desarrollo de aplicativo web basado en máquinas de vectores de soporte(svm) de aprendizaje supervisado para la predicción en la recomendación de cultivos mediante datos ambientales para fincas agroecológicas del cantón La Maná, provincia de Cotopaxi.

At present, artificial intelligence applied in the agricultural field follows a very successful trend in several areas within precision agriculture, including the detection of plant diseases and the prediction of plantations, to achieve these goals high-precision data and information and effective methods for an assessment of soil states are required. There are elements that must be taken into account, such as environmental variables, soil elements and PH; thus, becoming of great importance since there are large quantities of crops such as fruits and vegetables, which can reproduce with greater intensity depending on the description and characteristics of the soil for that planting. The present research project aims to make predictions of crop planting on agro ecological farms using supervised learning machine learning techniques and artificial intelligence models such as vector support machines (SVM), which will allow through an API to process the entry of environmental data to predict if the soil where the planting will take place is suitable for a certain crop through a web application which contains SVM models. Thanks to the development of this web application, technology is provided to the farmer to correctly execute the planting of his production that he requires in the future.

• 1. Verfasser: Coppiano Marín, Alex David (author)
• Weitere Verfasser: Herrera Vargas, Cristopher José (author)
• Format: bachelorThesis
• Sprache: spa
• Veröffentlicht: 2022
• Schlagworte: MODELOS; API; CULTIVOS; VARIABLES AMBIENTALES; MACHINE LEARNING; SISTEMAS DE INFORMACIÓN
• Online Zugang: http://repositorio.utc.edu.ec/handle/27000/8457