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https://doi.org/10.37815/rte.v34n3.948

Artículos originales

 

Estación meteorológica inteligente para control de riego y mitigación de heladas

Smart wea= ther station for irrigation control and frost mitigation

 

Geovany Lupercio1 <= /span>https://orcid.org/0000-0= 001-9103-3606,

Alberto Macancela1  https://orcid.org/0000-0= 003-1461-4364, Eduardo Tacuri2 https://orcid.org/0000-0= 002-4094-209X, Lucia Lupercio= 2 https://orcid.org/0000-0= 002-4798-6108

 =

1Universidad de Cuenca, Facultad de Ciencias Agropecuarias, Cuenca, Ecuad= or

glupercio@gmail.com, alberto.macancelah@ucuenca.edu.ec

 

1Universidad de Cuenca, Facultad de Ciencias Agropecuarias,<= span style=3D'mso-ansi-language:ES-EC'> Laboratorio de Geomática, Cuenca, Ecuad= or

eduardo.tacuri@ucuenca.edu.ec, lucia.lupercio@ucuenca.edu.ec

 

Enviado:         2022/06/19

Aceptado:       2022/09/21

Publicado:      2022/11/30                         

Resumen

Sumario: Introducción, Materiales y Métodos, Resultados y Discusión y Conclusiones.

 <= /o:p>

Como citar:<= /span> Lupercio, G., Macancela, A., Tacuri, E. & Lupercio, L. (2022). Estación meteorológica inteligente para control de riego y mitigación de helada= s. Revista Tecnológica - Espol, 34(3), 46-57. http://www.rte.espol.e= du.ec/index.php/tecnologica/article/view/948


En la agricultura, el agua es vital para el cultivo. Conocer cuándo regar y cuánto regar se puede responder técnicamente, a partir de datos provistos por estaciones meteorológicas. Estos datos no siempre están disponibles. Además= , si bien en el mercado existen controladores de riego, estos no están integrado= s a las estaciones y son de arquitectura cerrada. Por otro lado, el desarrollo = de la electrónica, la disponibilidad de sensores de costo asequible, protocolo= s, estándares y código abierto, facilitan la integración de componentes de hardware y software.  Este trabajo propone un prototipo de estación meteorológica inteligente que provee en ti= empo real datos de temperatura, humedad del ambiente, humedad del suelo, lluvia, como entrada para que un controlador active el riego en dos casos: i) por necesidad de agua para el desarrollo del cultivo; o ii= ) para mitigar heladas, apoyando al desarrollo sostenible agrícola con tecnol= ogía local, de código abierto y de costo asequible. Se aplicó la metodología bas= ada en prototipos rápidos, evaluando la operatividad de cada dispositivo electr= ónico y su integración en ambiente controlado, y luego en una parcela experimenta= l, en la granja Nero de la Universidad de Cuenca. Para el desarrollo se empleó hardware y software de código abierto, utilizando IDE de Arduino y Visual Studio Code. Para energizar se usó un panel sol= ar y baterías, optimizando el consumo energético. Este prototipo ha mostrado un funcionamiento continuo y estable, operando a 3100 m.s.n.m. Se continuará monitoreando y mejorando, para en el futuro poner a disposición de usuario = final.

 

= Pa= labras clave: = agricul= tura sostenible, Arduino, controladora SODAQ, sensores, riego autónomo.

 

Abstract

In agriculture, water is vital for the crop. Knowing when to irrigate and how much to irrigate can be answered technically from = data provided by weather stations. However, this data is not always available. In addition, although irrigation controllers are available on the market, they= are not integrated with the stations and have a closed architecture. On the oth= er hand, the development of electronics, the availability of affordable sensor= s, protocols, standards and open source, facilitate the integration of hardware and software components. This work proposes a prototype of an intelligent weather station that provides real-time data on temperature, ambient humidi= ty, soil moisture, and rainfall, as input for a controller to activate irrigati= on in two cases: i) due to the need of water for crop development; or ii) to mitigate frost, supporting sustainable agricultural development with local, open source and affordable technology. The methodology was applied based on rapid prototyping, evaluating the operability of each electronic device and= its integration in a controlled environment, and then in an experimental plot, = at the Nero farm of the University of Cuenca. Open-source hardware and software were used for the development, using Arduino IDE and Visual Studio Code. A solar panel and batteries were used to power the system, optimizing consumption. This prototype has shown continuous and stable operation at 31= 00 meters over the sea level. It will continue to be monitored and improved, in order to make it available to the end user in the future.=

 

Keywords: sustainable agriculture, Arduino, SODAQ controller, sensors, autonomous irrigation.

 

Introducción

Muchos de los avances tecnológicos aplicados al área agrícola en los últimos años, tienen como finalidad alcanzar la soberanía alimentaria, lo cual permite cu= brir la demanda de alimentos de la población (Iles & Montenegro d= e Wit, 2018). En Ecuador, el estado es el ente encarg= ado de garantizar la soberanía alimentaria (Vergara Romero & Mo= reno Silva, 2019). Para aportar a esto, una de las alterna= tivas es la aplicación de las nuevas tecnologías en la agricultura. Dichas tecnologías brindan un amplio abanico de posibilidades y están aplicándose principalmente en el monitoreo y manejo de cultivos, de esta manera se busca mayor productividad (Said Mohamed et al= ., 2021), mayor rentabilidad y el desarrollo sostenible.

 

La aplicación de las tecnologías de la información y comunicación (TIC) a la agricultura ha sido denominado agricultura inteligente (Bacco et al., 2019) o tecnologías agrícolas inteligentes (Kernecker et al., 2020); por ejemplo, se puede mencionar el uso = de drones, de internet de las cosas, sensores, la georreferenciación, entre ot= ros. La agricultura inteligente trata de conseguir la mayor eficiencia posible e= n la producción del cultivo al hacer uso de manera sostenible los bienes e insum= os (Knierim et al., 20= 19). Uno de los insumos más importantes para= el correcto desarrollo de cualquier cultivo es el agua.

 

En términos fisiológicos y agrícolas, el = agua en la planta tiene como finalidad el abastecer de humedad necesaria para el flujo de nutrientes y la disolución de sales presentes en el suelo, que, a = su vez permiten el crecimiento y desarrollo de la planta en un entorno favorab= le (Plett et al., 2020; Medrano et al., 2007). Cuando el agua lluvia no es suficiente,= se hace necesario contar con un sistema de riego para el óptimo desarrollo del cultivo. Sin embargo, determinar cuándo y cuánto regar en un cultivo, pueden ser preguntas simples de responder técnicamente, siempre y cuando se cuente= con la información necesaria. Es decir, para que un sistema de riego pueda brin= dar la cantidad de agua requerida y en los momentos correctos, se debe conocer ciertas variables edafológicas y agroclimáticas (Taha, 2018), como son la temperatura, precipitación, humedad ambiental, radiación solar, humedad del suelo. Estos datos son capturados por sensores incorporados en las llamadas estaciones meteorológi= cas (FAO, 1990), sin embargo no siempre están disponible= s, o son de acceso restringido.

 

Las estaciones meteorológicas y los siste= mas de riego convencionales, pueden representan un rubro económico alto; por lo que pueden ser solo costeados por pocos. Además, la limitación en la automatiza= ción de programas de riego es otra desventaja, pues estos no se adecuan a las necesidades que puede tener un cultivo en específico, en el momento oportun= o.

 

Con el uso de placas electrónicas de desa= rrollo, que traen una arquitectura y código abiertos, disponibles en el mercado a costos accesibles, se puede implementar estaciones meteorológicas personalizadas, controladores con diferentes fines para operar de forma autónoma. Esto brinda la oportunidad de construir esta propuesta de prototi= po de estación meteorológica inteligente para el control de riego y mitigación= de heladas, al disponer de los datos necesarios en tiempo real y realizar los cálculos de riego para otorgar al cultivo las condiciones de humedad necesa= rias para su desarrollo correcto.

 

Así, se aprovecha de manera técnica y sostenible el agua, especialmente en zonas en donde el recurso hídrico es escaso (Perry et al., 2017= ).  Por otra parte, un sistema de riego, puede ayudar a contrarrestar las heladas, que se trata de fenómenos que causan daños grave= s en los cultivos y facturan cuantiosas pérdidas económicas (Wassan et al., 2021). Al contar con una estación inteligente que controle el riego es posible activar el riego para la mitigación de las heladas, según las condiciones ambientales.

 

Materiales y Mét= odos

En esta invest= igación se trabajó con la metodología de prototipos rápidos. Se parte del levantami= ento de los requerimientos de las necesidades de agua para el cultivo, a partir = de los datos climatológicos y edafológicos requeridos, y de los parámetros par= a el manejo de heladas, considerando al riego por aspersión como un sistema de mitigación de heladas.

 

Se realizó un = análisis de los dispositivos electrónicos, considerando algunos factores, entre ellos los más importantes: que sean accesibles, de arquitectura abierta en cuanto= a hardware y software de tal forma que sea posible la integración con otros dispositivos de bajo consumo energético, de respuesta rápida y de precisión técnicamente aceptable para los fines de este trabajo.

 

Se diseñó una arquitectura provista de 3 componentes: Estación Meteorológica, Controlador= de Riego y Electroválvulas como se muestra en la Figura 1= . Se realizaron pruebas de operatividad d= e los dispositivos electrónicos, según las especificaciones de los fabricantes. A continuación, se construyeron prototipos rápidos que incluyen el diseño, interconexión, integración, desarrollo de software y pruebas de funcionamie= nto, para cada uno de los componentes, todo esto en ambiente controlado. Se real= izó la integración de los prototipos con las mejoras correspondientes. Finalmen= te, se integraron los 3 componentes y se pusieron en operación en ambiente real= en el campo.

 

Componente 1: Estación Meteorológica.<= /span>

La estación meteorológica está con formada por:

 

a)      Tarjeta Controladora “Solar D= ata Acquisition” (SODAQ) modelo mbili.

b)      Un conjunto de sensores que r= ecogen los datos de Temperatura y Humedad Ambiente, Temperatura del Suelo, Lluvia, Temperatura Interior y Humedad del Suelo.

c)      Suministro energético.

d)      Módulo de conectividad Blueto= oth.

 

Figura 1=

Arquitectura de la estación meteorológica inteligente para control de riego

 

Sensores

Para la Temper= atura y Humedad Ambiente se hizo uso del sensor SHT-31D, el mismo que se aloja al interior de una pantalla de Stevenson construida con platos invertidos que = lo protegen de la lluvia, el sol y asegura una ventilación adecuada. El Sensor= de Temperatura y Humedad SHT31-D se basa en un Chip sensor CMOSens, fabricado por Sensirion y totalmente calibrado, linealizado y cuenta con salida digital de temperatura compensada. Su funcionalidad incluye procesamiento de señal mejorado, dos direcciones I2C distintivas que son seleccionables por el usuario y con velocidades de comunicación de hasta 1 MHz. Amplio rango de tensión de alimentación de 2,1= 5 V a 5,5 V, lo cual garantiza la compatibilidad con diversas situaciones de montajes.

 

La especificac= ión de la humedad ambiente indica que su rango de operación es de 0 a 100% HR y tolerancia típica 2% HR. Mientras que, la especificación del sensor en que = se refiere a temperatura tiene un rango de operación -40 a 125 °C y tolerancia típica de 0.2°C (Sensiri= on, 2016). La Figura 2 muestra la tolerancia de la variación de= la temperatura en el rango de medición, observando que se mantiene constante h= asta los 85 ºC.

 

Para la medici= ón de la temperatura del suelo se empleó el Sensor DS18B20 con protección para agua,= es un sensor de temperatura de respuesta digital. La resolución del sensor de temperatura es configurable por el usuario a 9, 10, 11 o 12 bits.

 

 

Figura = 2=

Pruebas de tolerancia del sensor = SHT31-D

 

Para la medici= ón de la lluvia se usó el sensor de precipitaciones Davis 7857, en el cual la lluvia entra en el cono colector, se acumula en una cámara de cubeta basculante, e= sta se balancea al recolectar una cantidad de agua, igual al incremento en el q= ue mide el colector (0.01" o 0.2 mm) (Davis, = 2014). A medida que la cubeta se inclina, prov= oca el cierre de un interruptor y coloca en posición la segunda cámara de la cubeta basculante. El agua de lluvia sale por los desagües apantallados en la base= del colector. El número de descargas de las cubetas corresponde a la cantidad de aperturas y cierres del contacto del interruptor magnético.

 

Para la medici= ón de la humedad del suelo existen varios dispositivos de bajo costo; sin embargo, u= n reflectómetro en el dominio del tiempo (TDR) presta la facilidad de que es independiente a la composición de sales del terreno. Se realizó la comparación de funcionamiento del TDR económico VH-400 con el CS= 655 de Campbell Scientific, ambos mostrando medicio= nes muy similares; sin embrago la CS655 presenta mayores características mecáni= cas para operar en el campo.  En esta estación se empleó el reflectómetro TDR CS655.<= o:p>

 

El CS655 const= a de dos varillas de acero inoxidable de 12 cm de largo conectadas a una placa de circuito impreso. La placa de circuito está encapsulada en epoxi y se conec= ta un cable blindado a la placa de circuito para la conexión del registrador de datos. El CS655 mide el tiempo de propagación, la atenuación de la señal y = la temperatura. La permitividad dieléctrica, el contenido volumétrico de agua = y la conductividad eléctrica a granel se derivan luego de estos valores brutos. = El sensor utiliza para la salida el protocolo SDI-12 el cual está implementado= en 3 hilos; la alimentación que soporta el sensor está en el rango de 6 - 18Vd= c; con un consumo de corriente 80mA a 6Vdc (Campbel= l, 2022).

 

Suministro energético

La disponibili= dad de energía eléctrica en una estación meteorológica que va a ser emplazada en el campo es uno de los problemas con los cuales se debe lidiar. Se hizo uso de= un panel solar de 3 W-6 V, así como de una batería LiPo de 3.6V 3000mAh. Adicionalmente, se utilizó un convertidor DC-DC, para alca= nzar el voltaje de funcionamiento del TDR. Este convertidor se activará únicamen= te si recibe un requerimiento, optimizando el consumo energético.

 <= /p>

Módulo de conectividad bluetooth

En la estación= se ha incorporado un módulo bluetooth HC-05 para obtener los datos con el fin de realizar el monitoreo de todas las variables recolectadas por los sensores.= El módulo estándar consume 40mA y requiere para su funcionamiento de un voltaj= e superior a 3.3 V, disponible en la tarjeta controladora de la estación. Para lograr = el funcionamiento correcto se debió suprimir el regulador de 3.3V integrado al módulo HC-05 y energizarlo directamente al pin #12 suministrando el voltaje= de 3.3V. Para conectar a la estación mediante un enlace bluetooth y colectar l= os datos almacenados en la misma se empleó la aplicación “SerialBluetooth Terminal” que se puede descargar libremente.

 

Componente 2: Controlador de riego

La estación meteorológica supervisa en tiempo discreto= del comportamiento de las variables climáticas y del suelo que satisfacen los requerimientos de riego del cultivo e instruye al controlador de riego = las acciones a realizar de ser necesario. Este controlador de riego está confor= mado por un arduino nano, un banco de relés y baterí= a.

 

Arduino Nan= o

Arduino Nano es una placa de desarrollo de tamaño compact= o, completa y compatible con protoboards, basada e= n el microcontrolador ATmega328P. Tiene 14 pines de entrada/salida digital (de l= os cuales 6 pueden ser usando con PWM), 6 entradas analógicas, un cristal de 16Mhz, conexión Mini-USB, terminales para conexión ICSP y un botón de reseteo (Arduino.cc, 2021). Las programaciones para las órdenes de riego estarán alojadas en el código desarrollado para este dispositivo.

 

Componente 3: Electro - Válvula Hunter= con Solenoide Latch

Se utilizaron = tres electroválvulas disponibles en el mercado local marca Hunter. Estas funcion= an con solenoides de tipo enclavamiento mecánico, accionados por pulso eléctri= co, para de esta manera solventar los requerimientos de energía de las electroválvulas convencionales.

 

Operatividad de la estación meteorológ= ica inteligente

La estación meteorológica contiene como elemento central a la placa controladora Sodaq Mbili. Esta placa p= ermite configurar los requisitos del sistema mediante el desarrollo de código personalizado a los requerimientos del usuario. También permite gestionar sensores de varios tipos, mediante protocolos, para los cuales se ha desarrollado librerías que facilitan el trabajo. El Sensor de Temperatura y Humedad SHT31-D, se comunica con la placa controladora mediante una interface I2C que le permite tener tiempos de respuest= a de hasta 1Mhz.

 

Se lo ancla en= un soporte a 2 metros sobre el nivel de suelo en donde se desarrolla el cultiv= o, esta normativa ha sido dictada por la OMM (Oke, 20= 04). Mientras que, el sensor de temperatura = del suelo DS18B20, se instala enterrado a 10 cm de la superficie del suelo, en = la parcela experimental. La lluvia se registra mediante el conteo de las desca= rgas del balancín de pluviómetro, para esto se emplea una interrupción externa d= e la placa controladora, que suspende el código que esté ejecutando mientras ati= ende la petición de conteo de descargas.

 

Considerando q= ue el TDR CS655 está diseñado para funcionar con voltaje más alto del disponible = en la estación, se requirió emplear un “DC-DC up converte= r”, de esta manera se controla su encendido desde la placa controladora para los requerimientos de lectura del instrumento. Para establecer comunicación se utilizó una librería de código abierto SDI12.H que implementa el protocolo SDI-12 sobre la placa controladora. Finalmente, para el suministro energéti= co, la placa controladora dispone de un conector al que se le integra un panel solar de 3W – 6V para el suministro de energía durante el día, al mismo tie= mpo que dispone de otro conector al cual se le agrega una batería LiPo de 3000mAh a 3.7 V. El mantenimiento y carga de = la batería es controlada por el hardware con el que está equipado la placa controladora.

El datalogger o registrador de datos emplea como elemento de almacenamiento una memoria microSD externa instalada en el slot disponible de la placa controladora. P= ara el registro de los datos se adquiere la fecha y hora desde el reloj de tiem= po real RTC (DS3231) que está integrado en la controladora. Cada cinco minutos= se realiza una petición de lectura de todos los sensores anclados a la estació= n, con las mediciones reportadas se arma un set de datos al que se agrega fech= a y hora y se realiza la escritura en la memoria microSD. Los datos pueden ser descargados mediante conexión directa al puerto USB o mediante la facilidad bluetooth instalada en la estación para fines de monitoreo del buen funcionamiento de los sensores y otras aplicaciones para terceros.

 

Operatividad del Controlador de Riego<= /span>

El sistema de = riego requiere de capacidades sensoriales a fin de tomar decisiones y acciones acordes a las necesidades de riego de un determinado cultivo. Una estación meteorológica facilita estas capacidades al mismo tiempo que puede administ= rar un controlador de riego.

 

Para implement= ar la lógica de operación del controlador de riego se parte de los requerimientos funcionales. En esta investigación para determinar cuándo y cuánto regar, es decir establecer el plan de riego, se consideró el contenido volumétrico de agua (VWC, por sus siglas en inglés) a base de la capacidad de campo (CC), punto de marchitez permanente (PM) y umbral de riego (UR).  El sistema de riego se activa cuando el sensor de humedad del suelo registra que este ha llegado a UR (20%), y se detiene cuando el suelo alcanza la CC (25%).

 

Se recomienda = evitar ir por debajo del UR y mucho menos llegar a PM (15%) pues las plantas llegan a estresarse y pu= ede perderse el cultivo. Otros parámetros considerados para la automatización d= el riego son la hora del día, es de importancia considerarla, debido a que a m= edio día es contraproducente regar; además, si paralelo al riego en actividad existiesen eventos de precipitación importantes, la programación permitirá = que se desactive y deje de regar.

 

En esta invest= igación, el sistema de riego implementado en la parcela experimental, en donde opera= en ambiente real es riego por aspersión, el cual está conformado por tres grup= os de aspersores independientes. En este caso, este riego se está utilizando t= ambién para la mitigación de heladas. La literatura habla de heladas cuando la temperatura desciende bajo los cero grados centígrados, diferenciando la he= lada blanca de la negra, porque la segunda ocurre cuando además la humedad relat= iva es menor al 45% (Pérez M= orales, 2016). De aquí que, la estación inteligente cuando detecta estas condicio= nes envía señal al controlador para que se active el riego por intervalos mient= ras persistan las condiciones.

 

El controlador= tiene implementado la lógica para recibir órdenes de la estación y a partir de es= to realizar las acciones para el control de un banco de relés que permiten act= ivar o desactivar el flujo de agua en cada uno de los grupos de riego. Las válvu= las de los grupos de riego requieren de un breve pulso eléctrico para permitir o bloquear el flujo de agua.

 

Puesta en funcionamiento en ambiente r= eal

Una vez integr= ado el sistema de riego y la estación meteorológica inteligente (Figura 3= b), se puso en operación en la parcela experimental en la granja de Nero de la Universidad de Cuenca (Figura 3= a). Esta granja está ubicada a 3100 m s.n.m. En determinadas épocas se puede llegar a temperaturas bajo cero. El sistema de riego instalado en la parcela experimental es de aspersión con tres grupos de aspersores, sobre la parcel= a se tiene un cultivo de maíz (Zea mays) vari= edad zhima, con un clico fenológico aproximado de 270 días= .

Figura = 3=

a)      Ubicación parcela experimental b) Estación meteorológica intel= igente con sus componentes

<= span lang=3DES-US style=3D'font-size:3.0pt;mso-bidi-font-size:5.0pt;line-height:= 150%; mso-fareast-font-family:"Times New Roman";mso-fareast-theme-font:minor-fare= ast; mso-ansi-language:ES-US'> 

=

&n= bsp;

Resultados y Dis= cusión

La estación meteorol= ógica inteligente ha funcionado durante cuatro meses sin interrupciones. Tras la obtención de los datos de la estación semanalmente, para fines de monitoreo= , se realiza un análisis visual de las variables climáticas mediante el uso de gráficas de cajas y bigotes (Figura 4) para conocer si no hay valores atípicos o ruido= s, que podrían estar ligados al mal funcionamiento de los sensores.

 =

Figura <= /span>4

Gráfica de caja y bigotes de las variables medidas por la esta= ción meteorológica y consideradas para el riego automatizado

 <= /span>

Si bien la g= ráfica de caja y bigotes muestra valores atípicos en todas las variables medidas, = esto se considera normal debido a la ubicación geográfica en donde ha sido implementado el experimento. La temperatura ambiente registró valores bajos= de 4ºC y altos por encima de los 22ºC (Figura 4= a), la temperatura del suelo llegó a los 30ºC en los meses de marzo y abril (Figura 4= b).

 

La humedad relativa en los registros de la estación meteorológica refleja una amplia variabilidad de sus datos, estando el mínimo cerca del 50% y el máxi= mo alcanza el 100% durante los cuatro meses de monitoreo (Figura 4= c); al ser una zona alta puede llegar a humedades de ambiente bajas = que son comunes en zonas montañosas en donde se suelen registrar heladas, por debajo del 45%. Finalmente, la precipitación muestra eventos de importancia durante el mes de abril y mayo (Figura 4= d).

 

El sistema cada cinco minutos registra la lectura de los sensores, por lo que = para la gráfica de series temporales de las variables (Figura 5= ) se obtuvo las medias diarias por mes, a excepción de la precipitación, que es la suma diaria de las descargas. En la gráfica hay registros de datos desde el 17 de marzo hasta el 1 de junio para las variables climáticas, incluyendo temperatura del suelo; sin embargo, pa= ra la VWC se tiene registro desde el 19 de abril hasta el 1 de junio. El siste= ma no ha dejado de registrar datos durante los meses en operación, por lo que,= se encuentra la totalidad de los datos diarios recolectados.

 

Figura 5

Serie temporal de las variables medidas por la estación meteorológica

 <= /o:p>

En la series temporales se observan temperaturas ambiente= altas a finales de marzo, pero las más bajas a finales de abril y finales de mayo= (Figura 5= a). La humedad relativa más baja fue a inicios de mayo; las altas a finales de abril y a mediados de mayo (Figura 5= b). La temperatura del suelo fue alta a finales de marzo, mientras la más baja a inicios de junio  (Figura 5= c). Finalmente, las precipitaciones son altas a finales de marzo e inicios de abril, pero para fin de abril hasta mediados de mayo hay un decl= ive importante (Figura 5= d). El análisis del comportamiento de las variables descritas queda fuera del alcance de este estudio, sin embargo, podrían ser de mucha utilid= ad para otras investigaciones.

 

La Figura 6 muestra que el contenido volumétrico de agua durante el m= es de mayo estuvo por dos ocasiones por debajo del UR (20%) (Figura 6= a), por lo que el sistema de manera autóno= ma se activó para proveer de riego al cultivo de maíz hasta que el suelo nuevamente alcance la CC (25%). Asimismo, se identificó varias precipitacio= nes durante los meses de abril y mayo, por lo que la mayoría de tiempo el suelo= ha permanecido por encima de CC (Figura 6= b). Finalmente, el sistema de riego no se = ha activado para mitigar las heladas, debido a que las condiciones climáticas = no han sido las necesarias como para activar el riego, al considerar que, para= las heladas, la temperatura debe ser igual o por debajo de 0ºC y la humedad relativa igual o menor a 45%.

 

Figura 6

Valores medidos del VWC del suelo para la activación del riego automatizado<= /span>

 

Estos resultados, alientan el uso de plac= as del entrenamiento y sensores adaptados para aplicaciones en agricultura;  de la misma forma como lo demuestran los resultados de un sistema hidropónico automático (Ramady et al., 202= 1), proyecto basado en el microcontrolador Arduino nano, asistido por sensores, en donde también es posible monitorear variables y alcanzar autonomía.

 

Otras investigaciones demuestran que los = costos de un sistema comercial de riego y sus sensores son altos;  que unido a la limitada flexibilidad pa= ra adaptaciones no son una alternativa rentable económicamente para el agricul= tor promedio (Belayneh, Lea-Cox and Lichtenberg, 2013). Esto se enfatiza en países con agricult= ura menos tecnificada y-o en zonas de pequeños agricultores con limitados recur= sos económicos.

 

Conclusiones

En este trabaj= o se ha implementado una estación meteorológica inteligente, a nivel de prototipo, a partir dispositivos electrónicos con hardware y software de código abierto.= La estación ha sido personalizada para proveer datos de temperatura, humedad d= el ambiente, humedad del suelo y lluvia en tiempo real, como entrada para que = un controlador de riego trabaje de forma autónoma. Es decir, sea activado segú= n el plan de riego del cultivo, con el cual ha sido instruido. Adicionalmente, la estación meteorológica inteligente permite la activación del riego como mét= odo para mitigación de heladas, considerando que estos fenómenos pueden ocurrir= en alta montaña y pueden dañar el cultivo.

 

Este prototipo= ha sido probado, primero en ambiente controlado por partes y luego de forma integra= da en la parcela experimental. La parcela está ubicada en la granja Nero de la Universidad de Cuenca, sobre los 3100 msnm, en donde ha sido puesto en func= ionamiento, obteniendo resultados de operatividad satisfactorios. Sin embargo, para fut= uros desarrollos o incorporación de sensores adicionales, se podría tener la limitante de disponibilidad del hardware a nivel local. <= /p>

 

Por otra parte= , al considerar que un sistema de riego puede operar de acue= rdo a distintos parámetros y variables, entre ellos: la frecuencia de riego, el tiempo de riego, la humedad del suelo (CC y PM), temperatura de suelo, temperatura y humedad ambiente, etc., es decir, acorde a diferentes requeri= mientos funcionales y no funcionales; se plantea como trabajo futuro, el desarrollo= de una interfaz hombre-máquina intuitiva. Con ello, se busca satisfacerlas expectativas del usuario final (agricultor), con funcionalidad para modific= ar y calibrar variables consideradas para la planificación del riego según el cultivo.

 

Adicionalmente= , a futuro se plantea la integración a alguna plataforma de internet de las cos= as (IoT), empleando tecnologías para la transmisión inalá= mbrica de datos, de bajo consumo y largo alcance a fin de realizar un monitoreo re= moto de la estación meteorológica con datos en tiempo real.

 

Con este traba= jo se aporta al desarrollo sostenible de la agricultura, y la soberanía tecnológi= ca. Es decir, se pone tecnología local al alcance, que puede ser personalizada, según las necesidades del manejo del cultivo de una zona determinada. Adicionalmente, y no de menor importancia, se provee un banco de los datos climáticos que podrán servir para otros usos de la zona donde ha sido ubica= da la estación meteorológica inteligente.

 

Reconocimientos

Este trabajo h= a sido desarrollado en el marco del proyecto de investigación “Agricultura intelig= ente para el monitoreo y diagnóstico del cultivo de maíz (Zea mays)”, financiado entre la Universidad de Cuenca y la Corporación Ecuatoriana para= el Desarrollo de la Investigación y la Academia (CEDIA), para quienes los auto= res expresan agradecimiento.

<= o:p> 

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