Los estudiantes María Isabel Marín Henao, Jeyson Javier Borrero Domínguez y la docente Jennifer Paola Corredor Gómez del Semillero en Agricultura de Precisión- Grupo de Investigación Innovatic, hicieron su intervención en el International Week of Research, Developmen and Innovation con la ponencia que se reseña a continuación.
PONENCIA. Identifier Of Insects In Field Crops Based On Signal Segmentation.
RESEÑA. Lots of living beings exist in the field crops, from little ones like micro-organisms to big ones like plants and animals. One of the most important problem that farmers have are the plagues on their crops. This problem compromises important aspects such as the use of pesticides that affect the health of both farmers and the people that consume the food. Also the pesticides affect the ecosystems balance, they influence to the other living beings that are beneficial for the crops and the soil. The project aims to solve this issue by making the implementation of a detector system of insects in crops and reducing the use of pesticides in zones where is not needed. Through three important steps that are: pre-process that consists in a segmentation of the signal, the implementation of a special filter together with the FFT (Fourier Transform) and a characterization of the different signals, the training of different neural networks and the selection of the most optimal network, we were identified six different types of insects in the divers crops and plants in the Cundi–Boyacense savanna. The results based on the neural network selected and implemented in the project show a 5% error, for a 95% reliability in the identification of the insect sound, showing a basis for the development of environmental monitoring systems based in sound waves.
Keywords. Insects, neural network, digital signal processing, precision farming.
Contacto.
PhD. Ing. Jennifer Paola Corredor Gómez.
jennifer-corredor@upc.edu.co
