A large percentage of Colombia’s economic activity corresponds to the agricultural sector. In this sector, plantains rank second in production and planted area. However this crop is affected by different diseases, among which The Black Sigatoka stands out, caused by the fungus Mycosphaerella fijiensis. The disease highly reduces the production level of the crop and although there are prevention measures that allow reducing the incidence of the disease, there’s a lack of support for small producers in Colombia, who do not have technological tools to support the disease detection processes. This article outlines the development of a support system for the detection of black sigatoka using digital images. For this, a characterization process of the agricultural user is carried out, then, a machine learning methodology is implemented to classify the disease on a mobile device. The support system is validated through laboratory tests, field tests and the feedback from the agricultural user.
La red de sensores inalámbricos es una tecnología innovadora que ha tenido grandes impactos en el campo de la ingeniería, en los últimos años ha permitido desarrollos tecnológicos enfocados a la agricultura de precisión. En este artículo se describe la investigación que condujo al diseño de una red de multisensores inalámbricos de bajo costo para el registro y monitoreo de las variables sobre el estado de un cultivo, utilizando tarjetas de desarrollo Beaglebone Black, donde se han integrado sensores de temperatura, humedad relativa, humedad de suelo y cámaras digitales. La información adquirida se transmite —con el protocolo de comunicación inalámbrica Wireless Local Area Network (WLAN)— a un servidor central, permitiendo obtenerse un registro y control en una base de datos creada en Mysql con sistema operativo Linux. Los resultados de este trabajo permiten observar la confiabilidad y el consumo energético del equipo
The tendency in recent years to improve worldwide agricultural production has opened the door to innovative research techniques to prevent diseases, pests, and negative consequences due to climate variations in crops. This study aims to develop an acquisition system using the embedded BeagleBone Black and the DHT 22 sensor, which allow measuring the physical parameters of temperature and relative humidity; these were registered in a database that was created in MySQL. The system was implemented within a greenhouse crop; additionally, a mobile application was developed, written in Kotlin language, to facilitate monitoring the physical parameters of temperature and relative humidity remotely, so that farmers can collect valuable information about their crops wherever they are. This development was carried out using a client-server structure, making use of free software and hardware, which makes for a low-cost, easily-implemented system for farmers. The monitoring system worked as expected, and the information obtained was reliable. The results show that the implementation is useful in greenhouse agriculture and that, through digital innovation, effective agricultural practices can be improved which could increase production and decrease costs, making use of modern technologies.
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