Sistema de soporte de decisiones a la agricultura inteligente que incorpore aspectos de automatización de la fertirrigación y recomendaciones al agricultor

Descripción:

One of the biggest challenges for farmers is the prevention of disease appearance on crops. Governments around the world control border product entry to reduce the number of foreign diseases affecting local producers. Evenmore, it is also important to reduce the spread of crop diseases as quickly as possible and in early stages of propagation, to enable farmers to attack them on time, or to remove the affected plants. In this research, we propose the use of convolutional neural networks to detect diseases in horticultural crops. We compare the results of disease classification in images of plant leaves, in terms of performance, time execution, and classifier size. In the analysis, we implement two distinct classifiers, a densenet-161 pre-trained model and a custom created model. We concluded that for disease detection in tomato crops, our custom model has better execution time and size, and the classification performance is acceptable. Therefore, the custom model could be useful to use to create a solution that helps small farmers in rural areas in resource-limited mobile devices.

Tipo de publicación: Book Chapter

Publicado en: Advances in Sustainability Science and Technology

Descripción:

Smart farming solutions seek to help farmers in their daily activities. Their use has shown that it is beneficial for farmers to be aware of the distinct variables affecting the production. For this reason, having alerts and notifications in monitoring and control platforms is crucial. However, in some circumstances, farmers cannot attend to the messages delivered through traditional mechanisms, making it impossible for them to be informed at the right moment. In this paper, we present the design evaluation of an intelligent context-aware smart notifications system for precision agriculture. We consider using distinct notification mechanisms to improve the delivery of notifications to the farmers. We carry out an anticipated user experience evaluation to assess the system’s design and validate the use of the notification mechanisms in distinct scenarios. A total of 48 potential users from Spain and Costa Rica participated in the evaluation. The results show that our proposed system can be very helpful in supporting farmers to be aware of the state of crops. In addition, non-traditional notification mechanisms can potentially keep the farmers informed without affecting their daily activities. Costa Rican potential users value the system’s novelty more than Spanish users.

Tipo de publicación: Conference Paper

Publicado en: Proceedings of the International Conference on Ubiquitous Computing Ambient Intelligence (UCAmI 2022)