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Desarrollo de un sistema de monitoreo de cultivos basado en vehículos aéreos no tripul= ados y sensores RFID

 

Ángel Arcia Gil*1, Mateo Ramírez*2

1Profesor de Ingeniería Electrónica, Investigador, Universidad Católica Santa María La Antigua,

2Egresado de Ingeniería Electrónica, Investigador, Universidad Católica Santa María La Antigua.

 

*Autor para correspondencia. Email: aarciag@usma.com.pa

 

   =     Recibido: 05 de marzo de 2020 

Aceptado: 07 de abril de 2020

 

______________________= _______________________________________________________________Resumen

Aunque existen dive= rsos estudios y aplicaciones de drones y de sistemas rfid enfocados a mejorar la producción agrícola en otros países, la implementación en Panamá es prácticamente nula, ya que los sistemas de monitoreo son rudimentarios o en= su mayoría a base de observaciones físicas que consumen tiempo y que represent= an un elevado costo de horas-hombre. En este sentido, se desarrolló un prototipo de monitoreo de cultivos basado en vehículos aéreos no tripulados (drones) y sensores de humedad con tecnología de transmisión rfid (identificación por radio frecuencia), con el objetivo de mejorar los procesos en los ciclos de producción agrícola, reduciendo tiempo y costos a los productores nacionale= s, y potenciando el ahorro de pesticidas, agua y otras materias primas que hoy en día son administrados ineficientemente.

El presente trabajo detalla el diseño e implementación del prototipo con pruebas de los componentes individuales y prueba de concepto del sistema integrado, para monitorear cultivos de maíz en la Granja Escuela Casiciaco Haren Halde de la USMA (GECHA), ubicada en Las Minas, provincia de Herrera, para = en el futuro implementar el modelo en granjas de productores en la región de Azuero.

Palabras Clave: vehículos aéreos no tripulados, drones, sensores de humedad, sensores rfid, monitoreo de cultivos.

 

Abstract

Although several studies= and applications with drones and rfid systems already exist in other countries = to improve the agricultural production, the implementation in Panama is practically non-existent. This is due to the agricultural monitoring systems currently used are rudimentary and mostly based on time-consuming physical observations that represent a high = cost of man-hours. In this sense, a crop monitoring prototype was developed base= d on unmanned aerial vehicles (drones) and humidity sensors with rfid transmissi= on technology (radio frequency identification), with the aim of improving proc= esses in agricultural production cycles, reducing time and costs to national farm= ers, minimizing the use of pesticides, water and other raw materials that are cu= rrently inefficiently managed.

 

This paper details the design and implementation of the prototype, w= ith tests of the individual components and proof of concept of the integrated system, to monitor corn crops in the University Farm Casiciaco Haren Halde (GECHA) located in Las Minas, Herrera province, for a later implementation = in Azuero Farms.

Keywords: unmanned aerial vehicles, drones, humidity sensors, rfid sensors, c= rop monitoring

 =

1   Introducción =

Hoy en día = los productores nacionales no cuentan con tecnologías de punta que contribuyan = al mejoramiento de sus ciclos de producción, pues los métodos son rudimentario= s y basados meramente en observaciones visuales de los obreros y dueños de finc= as y granjas, incrementando así las probabilidades de que se pierdan cosechas, q= ue los costos de producción se mantengan relativamente altos, que se detecte de manera errónea y tardía las plagas, o que  la falta de irrigación no se determine  a tiempo. Otra parte del problema es que las tecnologías actuales que son utilizadas en otros países, no se ponen en práctica en el nuestro, por = el elevado nivel de inversión o por la complejidad de su uso; de aquí la importancia de implementar sistemas robustos y a la vez de bajo costo y fác= iles de manipular por los productores.

Diversas investigaciones se han estado realizando para diseñar sistemas novedosos capaces de medir variables de importancia agrícola. En [1-2] se muestra el diseño y fabricación de sensores de humedad de suelo impresos en papel y habilitado con tecnología rfid, con el objetivo de monitoreo de agua y cont= rol de irrigación, mientras que en [3] se utiliza tecnología rfid aplicada a la gestión de calidad de semillas producidas; esto con miras a desarrollar una agricultura inteligente (Smart-agriculture) cuya aplicación e impacto en los procesos de agrícolas tradicionales es evidente.

Además de la red de sensores desplegadas en el campo, otro elemento importante en un sis= tema de monitoreo agrícola es el lector que capta la información recopilada en dichos sensores. En los ejemplos mencionados anteriormente, los sensores diseñados y fabricados para pruebas experimentales tenían como opción de recolección de datos un lector rfid comercial fijo y a corta distancia para recopilar la información de los sensores. En [4] se plantea la posibilidad = de utilizar un lector rfid móvil, montado en un vehículo de granja o tractor, = para leer la data de sensores a pocos metros bajo la superficie, pero las características electromagnéticas del suelo, en especial el suelo mojado, i= mpacta negativamente el enlace de comunicación sensor-lector aumentando la pérdida= por “path loss” y afectando la velocidad a la que pudiese moverse el tractor co= n el lector incorporado.

Debido a es= to, se propone un sistema de lectura más ágil basado en vehículos aéreos no tripulados (Drones), herramienta tecnológica cuyas áreas de aplicaciones van desde monitoreo industrial, recolección de data científica, labores de búsq= ueda y rescate, entre otras.  Existen re= tos y limitantes con respecto al canal de comunicación aire-tierra, asignación espectral, vuelo de baja altura, estandarización y normativas requeridas. [= 5] Para las aplicaciones agrícolas, el uso de drones es cada más popular. Se plantea su utilización para por ejemplo distinguir las diferentes técnicas = de arado o evaluar el contenido clorofílico de las hojas a través de sensores RGB-D y técnicas de visión por computadora [6]. 

 =

2   Método Investigativo bas= ado en Entrevistas y Visitas Técnicas

En agosto d= e 2016, se realizaron entrevistas con los productores de maíz Elías Gálvez de Chitr= é, Herrera y David Monroy de Montijo, Veraguas, con el objetivo de entender có= mo monitorean actualmente sus cultivos y el nivel de tecnología utilizada para obtener mediciones y datos de sus cosechas.

Se confirma= ron las suposiciones iniciales de que se hace muy poco uso de tecnología para monitoreo, por diversas razones, entre las cuales están el costo de los dispositivos de medición, la complejidad técnica para manejarlos y la poca experiencia que se tiene en el país. Se hicieron pruebas de vuelo con el AR Drone 2.0 y al consultarles la idea del sistema a los productores, éstos mostraron su complacencia ante la facilidad de uso, aunque se mostraron cautelosos en cuanto al provecho que le puedan sacar.

 =

 =

 =

 =

 =

Fig. 1: Entrevistas con productores = de maiz en Herrera y Veraguas

 

También se = realizó entrevista técnica al Lic. Román Gordón de IDIAP, quien proveyó al proyecto= de valiosa información referente al maíz, enfatizando los siguiente:

·   &nb= sp;     El ciclo del crecimiento del maíz se divide en 4 etapas (0-30, 30-50, 50-80,80-100 días). De 0-30 días la falta de agua no afecta el desarrollo del maíz, mientras que entre 50-100 días, 25 mm de agua son necesarios.

·   &nb= sp;     La variable de humedad es de suma importancia y= se relaciona a la cantidad de lluvia (60 mm en día típico) con la humedad del suelo. El área de suelo donde se siembra el maíz necesitaría una condición = de máxima capacidad de suelo, y que la reposición de agua sería recomendada cu= ando se dé la condición de 1/3 de máxima capacidad de suelo.=

·   &nb= sp;     En IDIAP Azuero se utiliza el método manual o gravimétrico para calcular el % de humedad de suelo en el que se utiliza el peso como factor de comparación entre un extracto volumétrico de suelo en condición húmeda vs condición seca

·   &nb= sp;     Se utilizaron sensores y Data loggers marca Campbell a 3 pulgadas de profundidad para la medición de humedad en 2014, p= ero estos no funcionaron debido a que el nivel de humedad en ocasiones era tan = bajo que no se activaban los sensores (tierra muy seca).=

·   &nb= sp;     Para 2016 se planeaba la compra de un set de 10 sensores + lector marca Colepalmer para mediciones de humedad.=

·   &nb= sp;     Los métodos descritos anteriormente son métodos= en los que se requiere la intervención humana para recoger la información de c= ada data logger, por lo que el uso de sensores inalámbricos y un lector móvil embebido en un Dron resultaría de gran beneficio para las mediciones de hum= edad de suelo.

En mayo de 2016, se realizó la pri= mera visita técnica a la Granja Escuela Casiciaco Haren-Alde de la USMA, en Las Minas. El Ing. Jorge Castro, administrador de la granja, explicó que el con= trol de las siembras de maíz se hace a través de métodos visuales y no en base a tecnologías y comentó que una de las dificultades que presenta el crecimien= to del maíz es debido al “gusano cogollero” o especie Spodoptera frugiperda que afecta principalmente los cultivos de maíz y sorgo: durante los primeros dí= as de desarrollo de la planta, la larva puede actuar cortando la planta cerca = del suelo (como cortadora), o defoliándola parcial o totalmente, lo que puede causar la muerte de la misma. Durante el período de desarrollo vegetativo (6 hojas en adelante) el daño generalmente se circunscribe al cogollo (actuando como cogollera). En la última etapa del cultivo puede afectar la panoja, estigmas y granos. De acuerdo con el Ing. Castro, el contar con un dron pod= ría beneficiar el monitoreo y control de esta plaga a través de la cámara incorporada al dron e incluso incorporar un mecanismo para aplicar los quím= icos necesarios.

Otra aplicación posible según el Ing. Cas= tro es usar la cámara del dron para visualizar el color de la hoja del maíz. Ho= jas amarillas o descoloridas son indicación de que el maíz necesita una ración = de urea por falta de nitrógeno y que incluso el dron puede servir de mecanismo= de dispersión de la urea.

En agosto de 2016 se sostuvo una reunión con la Prof. Adelaida González, Directora de la= Granja con el objetivo de explorar posibilidades de colaboración con el centro.

Luego de efectuar vuelos de pruebas con el dron prototipo AR Dron 2.0, se hicieron l= as siguientes recomendaciones por parte de la Directora de la Granja:

·   &nb= sp;     Preparar 3 parcelas distintas de la granja para siembras de maíz con= 3 tipos de riego: riego por gravedad, riego por aspersores y riego por goteo<= o:p>

·   &nb= sp;     Hacer la instalación de los sensores de humedad inalámbricos simultáneamente en las 3 parcelas, para comparar los resultados de la cosec= ha y el impacto que tiene la variable de humedad en las mismas.

·   &nb= sp;     Coordinar con administrador de GECHA para determinar el estimado de materiales y presupuesto para la preparación de las 3 parcelas

·   &nb= sp;     Consultar con Ing. de IDIAP acerca del diseño del experimento.<= /o:p>

·   &nb= sp;     Utilizar las instalaciones del laboratorio de la granja para que los estudiantes hagan la calibración de los sensores con respecto a la textura = del suelo de la granja, el cual es en su mayoría arcilloso.

·   &nb= sp;     Realizar la instalación de los sensores + dron en el mes de enero, cuando es propicio sembrar maíz en la granja.

·   &nb= sp;     Hacer la instalación a otros productores una vez se haya comprobado = su funcionalidad en GECHA.

 =

=  

Fig.2: Visitas técnicas a Granja Granja Escuela Casicia= co Haren-Alde de la USMA, Las Minas, Herrera

 

Diseño de Sistema de Monitoreo – Análisis de Elementos

El análisis de los elementos principales del sistema se realizó desde el 2016, pasando por varias iteraciones hasta llegar a un sistema final en 201= 9.

El sistema de Monitoreo AgroDron se compone conceptualmente de tres gru= pos de elementos: 1-elementos de recolección de datos, elementos de lectura y e= lementos de análisis, como se especifica en la fig. 3.

Fig. 3: Diagrama Conceptual simplificado. Flujo de información entre elemento de captación de datos, elemento de lectura y elemento de análisis<= o:p>

 

Elementos de Datos:

·&nb= sp;        Sensores rfid: Se estipula como primera opción = el uso de rfid con capacidad de sensores de humedad del suelo, temperatura del suelo y conductividad eléctrica del suelo. La tecnología rfid o identificac= ión por radiofrecuencia es un método de comunicación altamente usado en el mundo actual y cuyas aplicaciones van desde el área logística, tiendas por departamento, hasta monitoreo de bienes y cultivos [1]. Los tipos de rfid a utilizados para este proyecto se detallan a continuación:=

·&nb= sp;        Sensor de humedad de suelo Hydro-H401 (Farsens): Sensor rfid UHF-tipo tag de humedad de suelo sin necesidad de batería. Este dispositivo cuenta con una placa sensor resistivo de humedad de suelo con r= ango de Ω a M-Ω dependiendo del nivel de humedad del suelo. El tag es compatible con lectores comercial EPC C1G2 rfid, no requiere hardware o comandos personalizados. Rango de Frecuencia de 860MHz-960MHz y rengo de lectura de 2m para 2W de EIRP [8].

·&nb= sp;        Sensor de humedad y temperatura Hygro-Fenix-H221 (Farsens): Sensor rfid UHF-tipo tag de hume= dad y temperatura. Cuenta con sensor HTS221 de humedad relativa (rango: 0%-100% humedad) y temperatura (rango: -30°C to +85°C) de ST Microelectronics. Rang= o de Frecuencia de 860MHz-960MHz y rengo de lectura de 2m para 2W de EIRP.

 

 

 

 

 

 

Fig. 4 Sensore= s de humedad Hydro-H401 y Humedad/Temperatura Hydro-Fenix-H221. Fuente http://www.farsens.com/

 

Elementos de Lectura:

Son 3 elementos de lectura definidos en el proyecto: antena, lector rfid y dron.

Antena: Existía la posibilida= d de utilizar una antena log-periódica comercial o diseñada en laboratorio para realizar la lectura de los tags desplegados en el terreno, con un rango de frecuencias de 400 - 1000 MHz, 6 dBi de ganancia y conector MMCX de 50 T= 86;. Se optó por una antena planar (patch-antena) Marca McI Wireless Edge con un peso de 0.5 kg el cual es manejable por el elemento de carga (dron).

 

 

 

(a)

(b)

(c)

 

Fig. 5: (a) Antena Log-Periódica. (b) Antena Planar. (c) Elementos de conexión

 

El segundo elemento dentro del sistema de lectura de datos es el lector= rfid, necesario para decodificar la data recibida de los sensores rfid. El lector utilizado para el proyecto AgroDron es el ThingMagic M6e UHF rfid, el cual = es el lo suficientemente pequeño y eficiente para ser usado en aplicaciones móviles, posee 4 puertos de operación a +31.5 dBm, además de interfaces ser= ial y USB. Tiene un Soporte multiprotocolo incluyendo EPCglobal Gen 2 (ISO 18000-6C, 4 puertos de 50 Ω conectores tipo MMCX para conexión de ant= enas, soporte de frecuencias de 860 a 960 MHz, niveles de lectura y escritura separados y ajustables por comando desde 5 dBm a 31.5 dBm (1.4W) con +/0.5 = dBm de precisión por encima de +15 dBm. Tiene una tasa de lectura de tags de 750tags/segundos a una distancia máxima de lectura de 9m con antena de 6dBi= .

El peso total del lector es de 0.3kg el cual es manejable por el dron.<= o:p>

 

 

<= /span>

<= /span>

(a)

Fig. 6: (= a) Lector rfid ThingMagic M6e. (b) Peso en kg

 =

El tercer elemento dentro del sistema de lectura de datos es el dron, el cual servirá como elemento de carga para la antena y el lector rfid. El vehículo aéreo no tripulado proveerá el mecanismo de lectura de información agrícola guardada= en la red de sensores rfid o proveerá la captura de imágenes a través de su cá= mara incorporada dependiendo del caso a aplicar. La utilización de este elemento conlleva variables inherentes al mismo que se tomaron en cuenta.=

·   &nb= sp;     Costo: Se consideraron 2 drones en escala económica baja (AR Drone) y escala económica Media (DJI) teniendo en cuenta el balance entre funcionali= dad y precio. El diseño y construcción de un dron no forma parte de esta Fase inicial del proyecto, pero es un ítem que se puede tomar en cuenta para fut= uras Fases.

·   &nb= sp;     Carga Total (elemento extra incorporado): Debido a que se incluirá un lector rfid comercial y/o una cámara (infraroja, térmica) como payload del dron, fue necesario analizar el peso de carga permitido por los Drones, sie= ndo el AR Drone AR adecuado para toma de imágenes y el Dron DJI para lectura rf= id.

·   &nb= sp;     Mecanismo de vuelo: Debido a que se intenta realizar un sistema atractivo para los productores y de fácil uso, se tomó en cuenta la implementación de sistemas de vuelo automático o pre-programados sumados la opción manual. (Existen diferentes opciones de código libre para el control= de vuelo del dron equipado con un módulo gps, como es el caso del Parrot Ar. D= ron 2.0 GPS Edition [6]. Se optó por lo opción manual en esta etapa del proyecto para reducir la complejidad de este.

·   &nb= sp;     Normativas sobre vuelo: Se tomó en cuenta las normativas actuales pa= ra el uso de drones a dependiendo de alturas de vuelo y peso, establecidas por= la Autoridad de Aeronáutica civil aunadas a las políticas de uso de frecuencia= s de comunicación reguladas por la Asep. Sólo el Dron DJI es necesario registrar= a nombre de USMA.

 

Basados en = lo anterior, los modelos de drones propuestos se detallan:

1.&n= bsp;     AR DRONE 2.0– GPS Edition. (Parrot):  Quadricopter controlado vía wifi con Tablet, celular o computadora. = En la edición GPS, una grabadora de vuelo está incluida.  Visualización 3D del vuelo, geolocaliza= ción con el módulo GPS. Batería de 1000mAh de Litio que provee hasta 12 minutos = de tiempo de vuelo más convenientes adaptadores para carga, sensores de presión para incremento de la estabilidad con software de aplicación AR. FreeFlight 2.0.  Este dron incorpora una Cámar= a frontal HD 720p permite al piloto ver exactamente lo que el dron ve, simulando esta= r en asiento de piloto con el uso del software AR. FreeFlight 2.0. Posee opción = de grabación de video e imágenes directamente en el dispositivo con el que se controla (celular, table, laptop) y con la opción de grabación en USB en el dron para videos más largos.

2.&n= bsp;     DJI S900: Este Dron es un Hexacoptero con un Landing Gear size de 460mm(L)×450mm(W)×360mm(H), posee un motor de 500W de Potencia máxima, con = un peso Takeoff de 4.7Kg ~ 8.2Kg, tiempo de Vuelo de 18 mins y temperatura de operación de -10 °C ~ +40 °C lo que lo hace adecuado para el proyecto AgroD= ron.

 =

 =

<= /span>

<= /span>

(a)

Fig. 7: Tipos de Drones utilizados en el diseño. (a) Ar Dron 2.0  y (b) DJI S900

 

Es importan= te recalcar que, para el proyecto, no se contempla usar la Cámara de este Dron (b), reduciendo el costo del mismo. El objetivo del Dron DJI es integrarle = el Lector rfid para toma de Datos.

 =

Elementos de Análisis

El último elemento en el diagrama conceptual, es el elemento de Análisis y procesamie= nto de Datos.

El prototipo requiere de un software instalado en Computador para poder trasladar los da= tos rfid de humedad en formato Hexadecimal para que puedan ser visualizados e interpretados de manera sencilla. Existen 2 posibilidades para prueba de Concepto:

Opción-1: Utilizar una laptop para instalación del software y conectarla a través de un cable USB al Lector rf= id montado en el Dron (Formato Umbilical) Fig. 8a

Opción-2: Esta opción contempla integrar = la computadora de procesamiento como elemento de carga en el Dron. El Rasberry= -Pi es una opción viable, sin embargo, se necesita considerar al aumento del presupuesto de Peso para el Dron.

 =

<= /span>

<= /span>

(a)

Fig.8.  Elementos de Análisis y procesamiento = de datos. (a) Umbilical, (b) Unidad integrada

 =

Para esta e= tapa del proyecto se optó por la opción-1.

 =

Elemento de Fabricación

Otros eleme= ntos externos fueron necesarios para el proyecto, como es el caso de la impresió= n 3D para acoplar el Lector y Antena al Dron.

·   &nb= sp;     Impresora MakerBot Replicator: Necesaria para acoplar el lector rfid= y antena al drone con materiales impresos. Fabricante: Rokit, stado: Tecnolog= ía: FDM – FFF, Materiales: PLA, ABS, Nylon, HIPS - Poliestireno de alto impacto, PVA (Polivinil Alcohol), Tamaño máximo de impresión: 290x205x255 mm, Espeso= r de capa:25 - 600 microns, Diámetro de boquilla:0,00mm. Precisión en posicionamiento eje XY: 11 micras (micrones)

 =

<= /span>

Fig. 9: Impresora MakerBot Replicator

 =

Diseño del Sistema e Integraciones

Una vez seleccionados los elementos individuales, se procedió a hacer el diseño de la integración de estos. El esquema general de integración se mue= stra en la fig. 10.

<= /span>

Fig. 10: Diversos acoplamientos debieron ser diseñados e impresos en = 3D para la integración entre elementos de los sistemas de datos, lectura y análisis =

 

Integración Antena + rfid tag + Sensor de Humedad a Soporte<= /span>

El tag rfid y antena del sensor deben est= ar a una altura aproximada de 1 m para facilitar la lectura por parte del lector integrado en Dron. Basado en esta referencia, se adhiere el tag rfid y ante= na a una base de 1m de altura la cual irá introducida a tierra junto con el sens= or (fig.11)

También fue necesario diseñar una cubierta protectora para aislar la antena del sensor, ante lluvia y polvo. Se realiza diseño e impresión 3D de 10cm x 5cm, sin afectar el patrón de radiación de = la antena rfid (fig. 12)

 

  <= /span>

<= /span>

(a)

(b)

 

Fig. 11. (a) Integración tag rfid y sensor de húmeda, (b) Integración= a base de 1m 

(a)

(b)

Fig 12: (a) diseño 3D cubierta de protección para antena. (b) Impres= ión 3D de cubierta

 

Integración de lector RFID y antena planar a dron=

Uno de los diseños más importantes del Proyecto es el acoplamiento del lector rfid y la antena planar al Dron. Para esto se tomó en cuenta dos importantes aspectos: el peso de carga añadida y= la estructura de acople.

Presupuesto de Carga: El Dron DJI S900 us= ado en este proyecto tiene un peso “takeoff” de 4.7kg ~ 8.2kg, y al realizar el presupuesto de carga se concluye que existe suficiente capacidad para agreg= ar el peso de la antena planar y lector rfid al Dron.

 

Análisis de Carga

Capacidad

Mínima (kg)

Máxima(kg)

Takeoff

4.7

8.2

Antena Planar

(0.5)

(0.7)

Lector rfid

(0.4)

(0.5)

Cables y accesorios

(0.1)

(0.2)

TTL

3.7

6.8

Tabla-1: Análi= sis de carga

Diseño de Acoplamiento: Se realizaron diversos diseños e impresiones 3D para el acoplamiento del lector rfid al D= ron (fig. 13), seleccionando el diseño (b) de columnas con abertura cuadrada.

Se requirió rediseñar y reforzar las unio= nes de la base de soporte a la estructura del Dron. Se hicieron varias pruebas = con tamaños, circunferencia y grosor (fig. 14)

(a)

(b)

(c)

(d)

(e)

Fig. 13. Diseños 3D de acoplamiento lector-dr= on. (a) plano-abertura rectangular, (b) columnas-abertura rectangular, (c) columnas-abertura cruz, (d) plano-hexa-abertura. (e) diseño Impreso final=

 

 

(a)

(b)

(c)

Fig 14. (a) diseño 3D de acoplamiento. (b) diseño final impreso en acoplado a sección frontal. (c) acoplamiento inferior

 

Diseño de Pruebas

Antes de realizar la integración de los elementos del sistema, se procedió a ejecutar pruebas individuales de los m= ismos, las cuales son detalladas a continuación.

Prueba de lectu= ra de tag rfid: La primera prueba consistió en leer los sensores de humedad rfid, con el lector rfid conectad= o a la aplicación de software para analizar los parámetros de salida.

Elementos necesarios: sensor rfid + tag, = antena+ lector rfid, software/laptop (fig. 15). La prueba resultó exitosa identific= ando los IDs de los tags. También se descargan los datos de lectura a tabla para análisis.

 

 

<= /i>

&n= bsp;

Fig 15. Prueba de lectura de tag rfid: se realiza lectu= ra correcta de tags ID con lector rfid a diversas distancias

 

Se hicieron pruebas para determinar la distancia máxima d entre la antena del lector rfid y el tag rfid

Tag ID<= o:p>

d(m)

Lectura=

&n= bsp;

Tag ID<= o:p>

d(m)

Lectura=

&n= bsp;

Tag ID<= o:p>

d(m)

Lectura=

000-1

1<= /o:p>

SI=

000-2

1<= /o:p>

SI=

000-3

1<= /o:p>

SI=

000-1

2<= /o:p>

SI=

000-2

2<= /o:p>

SI=

000-3

2<= /o:p>

SI=

000-1

3<= /o:p>

SI=

000-2

3<= /o:p>

SI=

000-3

3<= /o:p>

SI=

000-1

4<= /o:p>

SI=

000-2

4<= /o:p>

NO=

000-3

4<= /o:p>

NO=

000-1

5<= /o:p>

NO=

000-2

5<= /o:p>

NO=

000-3

5<= /o:p>

NO=

000-1

6<= /o:p>

NO=

000-2

6<= /o:p>

NO=

000-3

6<= /o:p>

NO=

Tabla-2: Análi= sis de distancia máxima=

Se determinó en base a las pruebas experimentales que la distancia máxima entre el Lector y el Tag rfid debe s= er de aproximadamente 3m +/- 1m para la correcta lectura. Esto es importante p= ara configurar la altura a la que volará el dron con respecto al a la antena de= l sensor una vez este esté en tierra.

 

<= /i>

&n= bsp;

Fig 16. Distancia máxima entre lector y sensor

 

Prueba de mediciones de Humedad

Esta prueba consiste en verificar que los sensores son capaces de detectar humedad y que ésta se pueda visualizar en = un formato adecuado. El esquema de la prueba se presenta en la fig. 17

 

Fig 17. Prueba de lectura de tag rfid: se realiza lectura en presenc= ia de tierra seca y húmeda

 

De acuerdo con la información proporciona= da por el fabricante, el sensor es resistivo con valores típicos de 100 ohm en presencia de suelo húmedo y valores típicos de 10Mohms en presencia de suelo seco. Esto se debe a que en un suelo húmero las partículas de agua permiten= la conductividad de corriente eléctrica, disminuyendo a su vez la Resistencia = del circuito Sensor-suelo. [12]

Una vez detectado el valor de Resistivida= d, este se transforma a % de Humedad de suelo según la siguiente fórmula [12]:=

=

Si bien es cierto, se pueden recolectar l= os valores numéricos y convertirlos a valores de % de humedad, existe una opci= ón más viable y sencilla de visualizar los datos a través de la interfaz gráfi= ca de usuario del software de lectura rfid. En la fig. 18 se muestran pruebas = con tierra seca y en la fig. 19 con tierra húmeda

 

 

 

Prueba de Resistencia de Acople Lector + Antena + Dron

Esta prueba consistió en verificar la resistencia del cople diseñado e impreso en 3D, de acuerdo al grosor de la impresión, peso de los componentes y ubicación en el dron. Las iteraciones y resultados se presentan en las tablas 3 y 4.

# Prueb= a

#1:

#2=

#3=

Carga

0 KG

0.5+0.4= +0.1=3D 1KG

0.5+0.4= +0.1=3D 1KG

Ubicaci= ón

Frontal=

Inferio= r

Frontal=

Vuelo

NO=

NO=

SI=

Imagen<= o:p>

Resulta= do

Pasó

Pasó

Falló

Comenta= rio

Tabla-3: Prueba de resistencia de acople con grosor inicial. Prototipo#1

 

# Prueb= a

#1:

#2=

#3=

Carga

0 KG

0.5+0.4= +0.1=3D 1KG

0.5+0.4= +0.1=3D 1KG

Ubicaci= ón

Frontal=

Inferio= r

Frontal=

Vuelo

NO=

NO=

SI=

Imagen<= o:p>

Resulta= do

Pasó

Pasó

Pasó

Comenta= rio

Tabla-4: Prueba de resistencia de acople con grosor inicial. Prototipo#2

 

3   Conclusiones

El presente trabajo, detalla el estudio y dis= eño de un sistema de monitoreo de humedad de suelo/cultivos con vehículos aéreo= s no tripulados y sensores rfid. El prototipo desarrollado logra validar la transferencia de información entre el elemento de recolección de datos y el elemento de análisis.

Se sugiere la implementación del sistema en la Finca GECHA de la USMA a través de un subsecuente proyecto de investigación= o en formato de Tesis con participación de estudiantes de Electrónica y estudiantes de Ciencias agrícolas

 =

4   Bibliografía

 =

[1] Sangkil Kim; Taolan Le; Tentzer= is, M.M.; Harrabi, A.; Collado, A.; Georgiadis, A., "An rfid-enabled inkjet-printed soil moisture sensor on paper for “smart” agricultural applications," in SENSORS, 2014 IEEE, vol., no., pp.1507-1510, 2-5 Nov. 2014

[2] Sangkil Kim; Traille, A.; Lee, = H.; Aubert, H.; Yoshihiro, K.; Georgiadis, A.; Collado, A.; Tentzeris, M.M., "Inkjet-printed sensors on paper substrate for agricultural applications," in Microwave Conference (EuMC), 2013 European, vol., no= ., pp.866-869, 6-10 Oct. 2013

[3] Li Hua; Wang Hong-jun; Shang Zh= en; Qing-Hua Li; Wei Xiao, "Application of rfid in agricultural seed quali= ty tracking system," in Intelligent Control and Automation (WCICA), 2010 = 8th World Congress on, vol., no., pp.3073-3077, 7-9 July 2010=

[4] Chuan Wang; George, D.; Green, P.R., "Development of plough-able rfid sensor network systems for precision agriculture," in Wireless Sensors and Sensor Networks (WiSNe= t), 2014 IEEE Topical Conference on, vol., no., pp.64-66, 19-23 Jan. 2014<= /o:p>

[5] Matolak, D.W., "Unmanned aerial vehicles: Communications challenges and future aerial networking,&qu= ot; in Computing, Networking and Communications (ICNC), 2015 International Conference on, vol., no., pp.567-572, 16-19 Feb. 2015

[6] Tripicchio, P.; Satler, M.; Dabisias, G.; Ruffaldi, E.; Avizzano, C.A., "Towards Smart Farming and Sustainable Agriculture with Drones," in Intelligent Environments (IE), 2015 International Conference on, vol., no., pp.140-143, 15-17 July 2015

[7] Johnson J.R.; “Will Drones Challenge Fixed And Handheld Rfid Readers In Retail?” rfid 24-7 Article, Au= gust 2014. Link

 [8] Choperena, M.; “Saving Water in Farm= ing Irrigation With Rfid Soil Moisture Sensors”. Farsens Blog Article, November 2013. Link

[9] University of California, Davis= , UC Drought Management: “Dielectric Soil Moisture Sensors” Link

[10] Choperena, M.; “rfid drones, really mobile and completely automated rfid readers”. Farsens Blog Article, November 2015. Link

[11] Wang J., Schluntz E., Otis G., Deyle T., “A New Vision for Smart Objects and the Internet of Things: Mobile Robots and Long-Range UHF rfid Sensor Tags”. arXiv:1507.02373v1 [cs.RO] Jul 2015

[12] http://www.farsens.com/en/prod= ucts/eval01-hydro-rm-h402

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Invest. Pens. Crit. (ISSN 1812-3864; e= ISSN 2644-4119)

DOI: = https://doi.org/10.37387/ipc.v8i2.142<= /o:p>

Vol. 8, No. 2, Mayo - Agosto 2020     <= /p>

pp. 27 - 43

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