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Framework for monitoring the temperature of aquaculture crops based on IOT
Framework para el monitoreo de la temperatura de cultivos acuícolas basado en IoT
DOI:
https://doi.org/10.15446/dyna.v88n218.90626Palabras clave:
Water quality, aquaculture monitoring, sensors, IOT (en)Calidad del agua, monitoreo de cultivos acuícolas, sensores, IOT. (es)
One of the current concerns in aquaculture is the management of the culture environment due to the impact that this generates, in the culture at production level, to the environment due to uncontrolled residues and in food safety, this concern is increasing due to the intensification of this activity in recent years which generates a high demand for food. Currently, many of the aquaculture processes are carried out manually, which requires cost in both time and resources, so this research, making use of technology, proposes a framework for full real-time temperature monitoring , configurable, scalable and low-cost by applying IOT, with the aim of optimizing the harvesting time and analysis of the crop status, which allows to support decision-making before the crop is affected.
Una de las preocupaciones actuales en la acuicultura es la gestión del ambiente del cultivo debido al impacto que este genera, en el cultivo a
nivel de producción, al ambiente por residuos no controlados y en la seguridad alimentaria, dicha preocupación va en aumento debido a la
intensificación de esta actividad en los últimos años la cual genera una alta demanda de alimentos. Actualmente, muchos de los procesos de la acuicultura se dan de forma manual, lo cual demanda costo tanto en tiempo como en recursos. En la presente investigación se propone un framework para el monitoreo de temperatura en tiempo real completo, configurable, escalable y de bajo costo aplicando la tecnología IoT, con el objetivo de optimizar el tiempo de recolección y análisis del estado del cultivo, lo cual permite dar soporte a la toma de decisiones antes de que el cultivo se vea afectado.
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1. Rubén Baena-Navarro, Yulieth Carriazo-Regino, Francisco Torres-Hoyos, Jhon Pinedo-López. (2025). Intelligent Prediction and Continuous Monitoring of Water Quality in Aquaculture: Integration of Machine Learning and Internet of Things for Sustainable Management. Water, 17(1), p.82. https://doi.org/10.3390/w17010082.
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