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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 1
Automated Irrigation System Using a Wireless Sensor Network and GPRS Module
Joaquín Gutiérrez, Juan Francisco VillaMedina, Alejandra NietoGaribay, and Miguel Ángel PortaGándara
Abstract— An automated irrigation system was developed tooptimize water use for agricultural crops. The system has adistributed wireless network of soilmoisture and temperaturesensors placed in the root zone of the plants. In addition, a gatewayunit handles sensor information, triggers actuators, and transmitsdata to a web application. An algorithm was developed withthreshold values of temperature and soil moisture that wasprogrammed into a microcontrollerbased gateway to controlwater quantity. The system was powered by photovoltaic panelsand had a duplex communication link based on a cellularInternetinterface that allowed for data inspection and irrigation schedulingto be programmed through a web page. The automated systemwas tested in a sage crop field for 136 days and water savings of upto 90% compared with traditional irrigation practices of theagricultural zone were achieved. Three replicas of the automatedsystem have been used successfully in other places for 18 months.Because of its energy autonomy and low cost, the system has thepotential to be useful in water limited geographically isolatedareas.
Index Terms— Automation, cellular networks, Internet,irrigation, measurement, water resources, wireless sensornetworks (WSNs).
I. INTRODUCTION
AGRICULTURE uses 85% of available freshwater resourcesworldwide, and this percentage will continue to be dominant in water
consumption because of population growth and increased fooddemand. There is an urgent need to create strategies based on science
and technology for sustainable use of water, including technical,agronomic, managerial, and
institutional improvements [1].There are many systems to achieve water savings in various
crops, from basic ones to more technologically advanced ones. Forinstance, in one system plant water status was monitored andirrigation scheduled based on canopy temperature distribution ofthe plant, which was acquired with thermal imaging [2]. Inaddition, other systems have been developed to schedule irrigationof crops and optimize water use by means of a crop water stressindex (CWSI) [3]. The empirical CWSI was first defined over 30years ago [4]. This index was later calculated
Manuscript received January 30, 2013; revised April 15, 2013; accepted May19, 2013. This work was supported by SAGARPACONACYT under Grant2009126183. The Associate Editor coordinating the review process was Dr.Subhas Mukhopadhyay.
The authors are with the Engineering Group, Centro de Investigaciones Biológicas del Noroeste, La Paz 23090, Mexico (email: joaquing04@cibnor.mx; jfvilla@cibnor.mx; anieto04@cibnor.mx;maporta@cibnor.mx).
Color versions of one or more of the figures in this paper are available onlineat http://ieeexplore.ieee.org.
Digital Object Identifier 10.1109/TIM.2013.2276487
using measurements of infraredcanopy temperatures, ambientair temperatures, andatmospheric vapor pressuredeficit values to determinewhen to irrigate broccoli usingdrip irrigation [5]. Irrigationsystems can also be automatedthrough information onvolumetric water content ofsoil, using dielectric moisturesensors to control actuators andsave water, instead of a predetermined irrigation scheduleat a particular time of the dayand with a specific duration. Anirrigation controller is used toopen a solenoid valve and applywatering to bedding plants(impatiens, petunia, salvia, andvinca) when the volumetricwater content of the substratedrops below a set point [6].
Other authors have reportedthe use of remote canopy temperature to automate cottoncrop irrigation using infraredthermometers. Through atimed temperature threshold,automatic irrigation wastriggered once canopytemperatures exceeded thethreshold for certain timeaccumulated per day.Automatic irrigationscheduling consistently hasshown to be valuable inoptimizing cotton yields andwater use efficiency withrespect to manual irrigationbased on direct soil watermeasurements [7].
An alternative parameter todetermine crop irrigationneeds is estimating plantevapotranspiration (ET). ET isaffected by weatherparameters, including solar
radiation, temperature, relative humidity, wind speed, and cropfactors, such as stage of growth, variety and plant density,management elements, soil properties, pest, and disease control[8]. Systems based on ET have been developed that allow watersavings of up to 42% on timebased irrigation schedule [9]. InFlorida, automated switching tensiometers have been used incombination with ET calculated from historic weather data tocontrol automatic irrigation schemes for papaya plants insteadof using fixed scheduled ones. Soil water status and ETbasedirrigation methods resulted in more sustainable practicescompared with set schedule irrigation because of the lowerwater volumes applied [10].
An electromagnetic sensorto measure soil moisture wasthe basis for developing anirrigation system at a savingsof 53% of water comparedwith irrigation by sprinklers in
an area of 1000 m2 of pasture[11]. A reduction in water useunder scheduled systems alsohave been achieved, using soilsensor and an evaporimeter,which allowed for theadjustment of irrigation to the
daily fluctuations in weatheror volumetric substratemoisture content [12].
A system developed formalting barley cultivations inlarge areas of land allowed forthe optimizing of irrigationthrough decision supportsoftware and its integrationwith an infield wirelesssensor network (WSN)driving an irrigation
00189456 © 2013 IEEE
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2 IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
machine converted to make sprinkler nozzles controllable. Thenetwork consisted of five sensing stations and a weather station.Each of the sensing stations contained a data logger with twosoil water reflectometers, a soil temperature sensor, andBluetooth communication. Using the network information andthe irrigation machine positions through a differential GPS, thesoftware controlled the sprinkler with application of theappropriate amount of water [13]. Software dedicated tosprinkler control has been variously discussed [14].
A data acquisition system was deployed for monitoring cropconditions by means of soil moisture and soil, air, and canopytemperature measurement in cropped fields. Data were downloadedusing a handheld computer connected via a serial port for analysisand storage [15]. Another system used to achieve the effectivenessof water management was developed based on a WSN and aweather station for Internet monitoring of drainage water usingdistributed passive capillary wicktype lysimeters. Water fluxleached below the root zone under an irrigated cropping systemwas measured [16]. There are hybrid architectures, wirelessmodules are located inside the greenhouse where great flexibilityis required, and wired modules are used in the outside area asactuator controllers [17].
The development of WSNs based on microcontrollers andcommunication technologies can improve the current methods ofmonitoring to support the response appropriately in real time for awide range of applications [18], considering the requirements ofthe deployed area, such as terrestrial, underground, underwater,multimedia, and mobile [19]. These applications involve militaryoperations in scenarios of battlefield, urban combat, and forceprotection, with tasks of presence, intrusion, ranging, imaging,detection of chemical, toxic material, biological, radiological,nuclear, and explosive [20], [21]. In addition, sensor networkshave been used in health care purposes for monitoring, alerting,assistance, and actuating with security and privacy to support realtime data transmission [22]. Vital sign monitoring, such as ECG,heart rate, body temperature, has been integrated in hospitals andhomes through wearable or etextile providing reports and alerts topersonal in case of emergency and tracking the location of patientswithin the hospital limits [23]. WSNs have been used to remotemonitor healthcare of dependent people at their homes throughseveral biomedical sensors such as ECG, blood pressure, bodytemperature [24], and body motion [25].
Home applications comprised wireless embedded sensors andactuators that enable monitoring and control. For comfort andefficient energy management, household devices have beencontrolled through sensors that monitor parameters such astemperature, humidity, light, and presence, avoiding waste ofenergy [26]. Sensor networks have been used for security purposes, based on several sensors such as smoke detectors, gassensors, and motion sensors, to detect possible risk situations thattrigger appropriate actions in response, such as send an alert to aremote center through wireless communication [27].
In industrial environments, WSNs have been installed to providerealtime data acquisition for inventory management, to equipmentmonitoring for control with appropriate actions, reducing human
errors and preventingmanufacturing downtime [28],[29]. For example, industrialWSN have been imple
mented to motor faultdiagnosis [30] and for themonitoring of thetemperaturesensitiveproducts during theirdistribution has been proposed[31]. In addition, there arewireless systems for structuralidentification underenvironmental an operationalparameters, such as load inbridges [32].
In environmentalapplications, sensor networkshave been used to monitor avariety of environmentalparameters or conditions inmarine, soil, and atmosphericcontexts [33]. Environmentalparameters, including humidity,pressure, temperature, soilwater content, and radiationwith different spatial andtemporal resolution and forevent detection such as disastermonitoring, pollutionconditions, floods, forest fire,and debris flow is continuouslymonitored [34]–[36].Applications in agriculture havebeen used to provide data forappropriate management, suchas monitoring of environmentalconditions like weather, soilmoisture content, soiltemperature, soil fertility,mineral content, and weeddisease detection, monitoringleaf temperature, moisturecontent, and monitoring growthof the crop, automatedirrigation facility and storage ofagricultural products [37]–[39].
Various commercial WSNsexist, ranging from limitedand lowresolution deviceswith sensors and embeddedprocessors to complete andexpensive acquisition systemsthat support diverse sensorsand include severalcommunication features [40].Recent advances inmicroelectronics and wirelesstechnologies created lowcostand lowpower components,which are important issues
especially for such systems such as WSN [41]. Powermanagement has been addressed in both hardware and softwarewith new electronic designs and operation techniques. Theselection of a microprocessor becomes important in poweraware design. Modern CMOS and microelectromechanicalsystems (MEMS) technologies allowed manufacturers toproduce on average every three years a enhance generation ofcircuits by integrating sensors, signal conditioning, signalprocessing, digital output options, communications, and powersupply units [42], [43]. For example, the parallel combinationof a battery and a supercapacitor has been used to extend theruntime of lowpower wireless sensor nodes [44].
Energy harvesting mechanisms have been employed, in caseswhere it is difficult for changing or recharging batteries, hence thisstrategy has involved combining it with efficient powermanagement algorithms to optimize battery lifetime. Power
harvesting is a complementaryapproach that depends onambient energy sources,including environmentalvibration, human power,thermal, solar, and wind thatcan be converted into useableelectrical energy [45]–[47]. Onthe other hand, severalstrategies have beenimplemented to reduce powerconsumption, such as poweraware protocols, resource andtask management,communication, topologycontrol and routing, models
based on events, and congestioncontrol mechanism to balancethe load, prevent packet drops,and avoid network deadlockusing a combination ofpredeployed group keys thatallow the dynamic creation ofhigh security subnetworks andoptimizes energy efficiency ofsensor networks [48], [49]. Forinstance, energysavingstrategies have been achievedthrough scheduling [50], [51],sleep or wake up schemes, andadaptive radio frequency (RF)in nodes, and choosing
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GUTIÉRREZ et al.: AUTOMATED IRRIGATION SYSTEM USING A WSN AND GPRS MODULE 3
a network configuration [52]. There are also algorithms tomaximize the network coverage ratio with a predefined balancethe energy consumption in the whole WSN [53], to reduce boththe transmission and the computational loads at the node level[54], and to estimate online the optimal sampling frequenciesfor sensors [55].
In a wireless node, the radio modem is the major powerconsuming component; recently, wireless standards have beenestablished with medium access control protocols to providemultitask support, data delivery, and energy efficiency performance [56], such as the standards for wireless local areanetwork, IEEE 802.11b (WiFi) [57] and wireless personal areanetwork (WPAN), IEEE 802.15.1 (Bluetooth) [58], IEEE802.15.3 (UWB) [59], and IEEE 802.15.4 (ZigBee) [60], andthose open wireless communication standards for Internet protocol version 6 (IPv6) over lowpower wireless personal areanetworks 6LoWPAN [61], [62], wireless highway addressableremote transducer WirelessHART [63], and ISA100.11a [64]developed by the International Society of Automation.
In this paper, the development of the deployment of anautomated irrigation system based on microcontrollers and wirelesscommunication at experimental scale within rural areas ispresented. The aim of the implementation was to demonstrate thatthe automatic irrigation can be used to reduce water use. Theimplementation is a photovoltaic powered automated irrigationsystem that consists of a distributed wireless network of soilmoisture and temperature sensors deployed in plant root zones.Each sensor node involved a soilmoisture probe, a temperatureprobe, a microcontroller for data acquisition, and a radiotransceiver; the sensor measurements are transmitted to amicrocontrollerbased receiver. This gateway permits theautomated activation of irrigation when the threshold values of soilmoisture and temperature are reached. Communication between thesensor nodes and the data receiver is via the Zigbee protocol [65],[66] under the IEEE 802.15.4 WPAN. This receiver unit also has aduplex communication link based on a cellularInternet interface,using general packet radio service (GPRS) protocol, which is apacketoriented mobile data service used in 2G and 3G cellularglobal system for mobile communications (GSM). The Internetconnection allows the data inspection in real time on a website,where the soilmoisture and temperature levels are graphicallydisplayed through an application interface and stored in a databaseserver. This access also enables direct programming of scheduledirrigation schemes and trigger values in the receiver according thecrop growth and season management. Because of its energyautonomy and low cost, the system has potential use for organiccrops, which are mainly located in geographically isolated areaswhere the energy grid is far away.
II. AUTOMATED IRRIGATION SYSTEM
The automated irrigation system hereby reported, consisted oftwo components (Fig. 1), wireless sensor units (WSUs) and awireless information unit (WIU), linked by radio transceivers thatallowed the transfer of soil moisture and temperature data,implementing a WSN that uses ZigBee technology. The WIU has
also a GPRS module to transmitthe data to a web
Fig. 1. Configuration of theautomated irrigation system. WSUsand a WIU, based on microcontroller,ZigBee, and GPRS technologies.
Fig. 2. WSU. (a) Electronic component PCB. (b) Radio modem ZigBee.(c) Temperature sensor. (d) Moisture sensor. (e) Rechargeable batteries.(f) Photovoltaic cell. (g) Polyvinyl chloride container.
server via the public mobilenetwork. The information canbe remotely monitored onlinethrough a graphicalapplication through Internetaccess devices.
A. Wireless Sensor Unit
A WSU is comprised of a RFtransceiver, sensors, amicrocontroller, and powersources. Several WSUs can bedeployed infield to configure adistributed sensor network forthe automated irrigation system.Each unit is based on themicrocontroller
PIC24FJ64GB004 (Microchip Technologies, Chandler, AZ) thatcontrols the radio modem XBee Pro S2 (Digi International, EdenPrairie, MN) and processes information from the soilmoisturesensor VH400 (Vegetronix, Sandy, UT), and the temperaturesensor DS1822 (Maxim Integrated, San Jose, CA). Thesecomponents are powered by rechargeable AA 2000mAh NiMHCycleEnergy batteries (SONY, Australia). The charge is
maintained by a photovoltaicpanel MPT4.875 (PowerFilmSolar, Ames, IN) to achieve fullenergy autonomy. Themicrocontroller, radio modem,rechargeable batteries, andelectronic components were
encapsulated in a waterproofPolyvinyl chloride (PVC)container (Fig. 2). Thesecomponents were selected tominimize the powerconsumption for the proposedapplication.
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4 IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
Start
Request ConnectionGet date/time
date and time WIU
INT-RTCC?
Yes
EnableVoltage
Regulator
Measure:MoistureTemperatureVoltage
Package/Senddata to WIU
DisenableVoltage
Regulator
Sleep Mode
Fig. 3. Algorithm of wireless sensor unit (WSU) for monitoring the soilmoisture and temperature.
1) SingleChip PIC24FJ64GB004: A 16bit microcontrollerwith 44pins and nanoWatt XLP technology that operates in arange 2.0 to 3.6 V at 8 MHz with internal oscillator. It has up to25 digital input/output ports, 13, 10bit analogtodigitalconverters (ADC), two serial peripheral interface modules, twoI2C, two UART, 5 16bit timers, 64 KB of program memory, 8KB of SRAM, and hardware realtime clock/calendar (RTCC).The microcontroller is well suited for this remote application,because of its lowpower operating current, which is 175 µA at2.5 V at 8 MHz and 0.5 µA for standby current in sleep modeincluding the RTCC.
The microcontroller was programmed in C compiler 4.12(Custom Computer Services, Waukesha, WI) with the appropriate algorithm (Fig. 3) for monitoring the soilmoisture probethrough an analogtodigital port and the soiltemperature probethrough another digital port, implemented in 1Wirecommunication protocol. A battery voltage monitor is includedthrough a highimpedance voltage divider coupled to an analogtodigital port. The data are packed with the correspondingidentifier, date, and time to be transmitted via XBee radiomodem using a RS232 protocol through two digital portsconfigured as transmitter (TX) and receiver (RX), respectively.After sending data, the microcontroller is set in sleep mode forcertain period according to the sensor sampling rate desired,whereas the internal RTCC is running. This operation mode
allows energy savings. Whenthe WSU is launched for firsttime, the algorithm alsoinquires the WIU,
Fig. 4. Communication frames between a WSU and the WIU.
the date and time to program the RTCC, and periodically updates it for synchronization.
2) ZigBee Modules: ZigBee(over IEEE 802.15.4) technology is based on short rangeWSN and it was selected forthis batteryoperated sensornetwork because of its lowcost, low power consumption,and greater useful range incomparison with otherwireless technologies likeBluetooth (over IEEE802.15.1), UWB (over IEEE802.15.3), and WiFi (overIEEE 802.11) [67]. TheZigBee devices operate inindustrial, scientific, andmedical 2.4GHz radio bandand allow the operation in asocalled mesh networkingarchitecture, which can bedifferentiated into threecategories: 1) coordinator; 2)router; and 3) end device.
From a wide range ofcommercial ZigBee devices,the XBeePRO S2 is anappropriate originalequipment manufacturermodule to establishcommunication between aWSU and the WIU because ofits longrange operation andreliability of the sensornetworking architecture. TheXBeePRO S2 is a RF modemwith integrated chip antenna,20pins, and 13 generalpurpose input/output (GPIO)ports available of which fourare ADC. It can operate up toa distance of 1500 m inoutdoor lineofsight with 170
mA of TX peak current and 45 mA for RX current at 3.3 V andpowerdown current of 3.5 µA.
The XBee radio modem of each WSU is powered at 3.3 Vthrough a voltage regulator ADP122AUJZ3.3R7 (AnalogDevices, Norwood, MA) and interfaced to the host microcontroller through its serial port, a logiclevel asynchronous serial,and voltage compatible UART configured at 9600 baud rate, no parity, 1 start bit, 1 stop bit, 8 data bits.
The WSUs were configured such as end devices to deploy anetworking topology pointtopoint based on a coordinator thatwas implemented by the XBee radio modem of the WIU. An enddevice has the following characteristics: 1) it must join a ZigBeePAN before it can transmit or receive data; 2) cannot allow devices
to join the network; 3) mustalways transmit and receive RFdata through its parent; 4)cannot route data; and
5) can enter low power modesto conserve power and can bebattery powered. The leastsignificant byte of the unique64bit address is used to labelthe information of the soilmoisture and temperature foreach WSU in the network.This byte is registered in the
WIU as the identifier (ID)associated to each WSU. Asshown in the sample frames torequest date/time, receivedate/time, and send datapackaged to the WIU (Fig. 4).
3) Soil Sensor Array: Thesensor array consists of two soilsensors, including moisture andtemperature that are inserted inthe root zone of the plants. TheVH400 probe was selected to
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GUTIÉRREZ et al.: AUTOMATED IRRIGATION SYSTEM USING A WSN AND GPRS MODULE 5
estimate the soil moisture because of low power consumption(< 7 mA) and low cost. The probe measures the dielectricconstant of the soil using transmission line techniques at 80MHz, which is insensitive to water salinity, and provides anoutput range between 0 and 3.0 V, which is proportional to thevolumetric water content (VWC) according to a calibrationcurve provided by the manufacturer. The sensor was powered at3.3 V and monitored by the microcontroller through an ADCport.
Soil temperature measurements were made through the digital thermometer DS1822. The sensor converts temperature to a12bit digital word and is stored in 2B temperature registers,corresponding to increments of 0.0625 °C. The temperature isrequired through a reading command and transmitted using 1Wire bus protocol implemented in the microcontroller throughone digital port. The thermometer has ±2.0 °C accuracy over−10 °C to +85 °C temperature range and a unique 64bit serialnumber. The sensor is a 3pin singlechip and TO92 packagethat was embedded in a metal capsule and sealed in awaterproof PVC cylindrical container.
To calibrate the soil moisture, several samples were preparedwith 1 kg of dry soil from the crop area. Its composition wasloamy sand with 80% sand separate, 4.5% clay separate, and15.6% silt separate. The soil water holding capacity was of20.7% VWC corresponding to measured output voltages of1.45 V. The temperature sensors were calibrated through areference mercury thermometer CT40, with 0.1 °C divisionsand a range from −1 °C to 51 °C. The thermometer and thetemperature sensors were placed in an insulated flask filled withmineral oil at 10 °C and 40 °C.
4) Photovoltaic Cell: To maintain the charge of the WSUbatteries, a solar panel MPT4.875 was employed. Each solarpanel delivers 50 mA at 4.8 V, which is sufficient energy tomaintain the voltage of the three rechargeable batteries. AMSS1P2U Schottky diode (Vishay, Shelton, CT) is used toprevent the solar module and to drain the battery when is in thedark. The solar panel is encapsulated in a 3mm clear polyesterfilm with dimensions of 94 mm × 75 mm. This flexible panelwas mounted on a PVC prismatic base (100 mm × 80 mm ×3.17 mm) that is fastened in the upper part of a PVC poleallowing for the correct alignment of the photovoltaic panel tothe sun. The stick is 50 cm of length and 12.5 mm of diameter;the lower end of the pole had a tip end to be buried.
B. Wireless Information Unit
The soil moisture and temperature data from each WSU arereceived, identified, recorded, and analyzed in the WIU. TheWIU consists of a master microcontroller PIC24FJ64GB004, anXBee radio modem, a GPRS module MTSMCG2SP(MultiTech Systems, Mounds View, MN), an RS232 interfaceMAX3235E (Maxim Integrated, San Jose, CA), two electronicrelays, two 12 V dc 1100 GPH Livewell pumps (RuleIndustries, Gloucester, MA) for driving the water of the tanks,and a deep cycle 12 V at 100Ah rechargeable battery L24M/DC140 (LTH, Mexico), which is recharged by a solar
panel KC130TM of 12 V at130 W (Kyocera, Scottsdale,AZ)
Fig. 5. WIU. (a) Electronic component PCB. (b) Master microcontroller.
(c) Solid state memory. (d) Opticalisolators. (e) RS232 interface. (f)Push button. (g) Output cables topumps. (h) Supply cable from chargecontroller.(i) PCV box.
through a PWM chargecontroller SCI120 (Syscom,Mexico). All the WIUelectronic components wereencapsulated in a waterproofPVC box as shown in Figs. 5and 6. The WIU can belocated up to 1500m lineofsight from the WSUs placedin the field.
1) Master Microcontroller:The functionality of the WIUis based on themicrocontroller, which isprogrammed to performdiverse tasks, as is shown inFig. 7. The first task of theprogram is to download froma web server the date and timethrough the GPRS module.The WIU is ready to transmitvia XBee the date and timefor each WSU once powered.
Then, the microcontroller receives the information packagetransmitted by each WSU that conform the WSN.
These data are processed by the algorithm that first identifies theleast significant byte of a unique 64bit address encapsulated inthe package received. Second, the soil moisture and temperaturedata are compared with programmed values of minimum soilmoisture and maximum soil temperature to activate the irrigationpumps for a desired period. Third, the algorithm also records a log
file with the data in a solid statememory 24FC1025 (MicrochipTechnologies, Chandler, AZ)with a capacity of 128 kB. Eachlog is 12B long, including soilmoisture and temperature, thebattery voltage, the WSU ID,the date, and time generated by
the internal RTCC. If irrigationis provided, the program alsostores a register with theduration of irrigation, the date,and time. Finally, these dataand a greenhouse ID are alsotransmitted
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6 IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
Fig. 6. Inside view of the WIU. (a) Radio modem ZigBee. (b) GPRS module.(c) SIM card. (d) GPRS PCB antenna. (e) Pumps relays.
Fig. 7. Algorithm of the master microcontroller in the WIU for the automatedirrigation system.
at each predefined time to a web server through HTTP via theGPRS module to be deployed on the Internet web application inreal time.
When the server receives a request for the web page, itinserts each data to the corresponding field in the database.
This link is bidirectional and permits to change the thresholdvalues through the website interface; scheduled watering orremote watering can be performed.
The WIU has also a push button to perform manual irrigation for a programmed period and a LED to indicate when theinformation package is received. All the WIU processes can bemonitored through the RS232 port.
The WIU includes a function that synchronizes the WSUs atnoon for monitoring the status of each WSU. In the case that all
WSUs are lost, the systemgoes automatically to adefault irrigation schedulemode. Besides this action, anemail is sent to alert thesystem administrator.
2) GPRS Module: TheMTSMCG2SP is a cellularmodem embedded in a 64pins universal socket thatoffers standardsbased quadband GSM/GPRS Class 10performance. This GPRSmodem includes an embeddedtransmission controlprotocol/Internet protocolstack to bring Internetconnectivity, a UFL antennaconnector and subscriberidentity module (SIM) socket.The module is capable oftransfer speeds up to 115.2 Kb/s and can be interfaceddirectly to a UART ormicrocontroller using ATcommands. It also includes anonboard LED to displaynetwork status.
The GPRS was powered to 5V regulated by UA7805 (TexasInstruments, Dallas, TX) andoperated at 9600 Bd through aserial port of the mastermicrocontroller and connectedto a PCB antenna. The powerconsumption is 0.56 W at 5 V.
In each connection, themicrocontroller sends ATcommands to the GPRSmodule; it inquires the receivedsignal strength indication,which must be greater than −89dBm to guarantee a goodconnection. In addition, itestablishes the communicationwith the URL of the web serverto upload and download data. Ifthe received signal strength ispoor, then all data are storedinto the solidstate memory ofthe WIU and the system try toestablish the connection eachhour.
3) Watering Module: Theirrigation is performed bycontrolling the two pumpsthrough 40A electromagneticrelays connected with themicrocontroller via twooptical isolators CPC1004N(Clare, Beverly. MA). Thepumps have a powerconsumption of 48 W each
and were fed by a 5000l water tank. Four different irrigation actions (IA) are implemented in the
WIU algorithm:
1) fixed duration for manual irrigation with the push button;
2) scheduled date and time irrigations through the web pagefor any desired time;
3) automated irrigation with a fixed duration, if at least onesoil moisture sensor value of the WSN drops below theprogrammed threshold level;
4) automated irrigation with a fixed duration, if at least onesoil temperature sensor value of the WSN exceeds theprogrammed threshold level.
3. Web Application
Graphical user interfacesoftware was developed forrealtime monitoring andprogramming of irrigationbased on soil moisture andtemperature data. Thesoftware application permitsthe user to visualizegraphically the data from eachWSU online using any devicewith Internet (Fig. 8).
Besides the soilmoistureand temperature graphs, theweb application displays thetotal water consumption andthe kind of the IA.
The web application alsoenabled the user directprogramming of scheduledirrigation schemes andadjusting the trigger values inthe WIU according to the cropspecies and seasonmanagement. All theinformation is stored in adatabase. The web applicationfor monitoring andprogramming was coded inC# language of MicrosoftVisual Studio 2010. Thedatabase was implemented inSQL Server 2005.
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GUTIÉRREZ et al.: AUTOMATED IRRIGATION SYSTEM USING A WSN AND GPRS MODULE 7
Fig. 8. Web application of the automated irrigation system to remotelysupervise the soil moisture and temperature of each WSU and change thethreshold values and the scheduled irrigation.
Fig. 9. Greenhouse for organic sage production with WSUs located arbitrarilyin different cultivation beds. (a) WSU55 on bed 2. (b) WSU56 on bed 12.(c) WSU57 on bed 23. WSU54 was on bed 1.
III. IRRIGATION SYSTEM OPERATION
The system was tested in a 2400m2 greenhouse, located nearSan Jose del Cabo, Baja California Sur (BCS), Mexico (23°10.841’ N, 109° 43.630’ W) for organic sage (Salviaofficinalis) production. The greenhouse had 56 production bedscovered with plastic. Each bed was 14m long andhad two black polyethylene tubes with drip hole spacing of 0.2 m. The automated irrigation system was used
to irrigate only 600 m2, which corresponded to 14 beds;whereas, the remaining 42 beds were irrigated by humansupervision to compare water consumption with the traditionalirrigation practices in this production place. Four WSUs labeledby the last significant byte of the unique 64bit address (WSU54, 55, 56, and 57) were located in the greenhouse at arbitrarypoints (Fig. 9).
The WSU57 unit was used to measure the soil moisture andtemperature in the area (bed 23) where the traditional irrigationpractices were employed. The other three units (WSU54, 55, and56) were located in beds 1, 2, and 12 to operate the automated
irrigation system with theircorresponding soil moisture andtemperature sensors situated ata depth of 10 cm
Fig. 10. Gathered data of the WSUs,in the web application of theautomated irrigation system: soiltemperatures, soil moisture, and watersupplied (vertical bars indicateautomated and scheduled irrigation).
in the root zone of the plants.These three units allowed dataredundancy to ensureirrigation control. Thealgorithm considered thevalues from the WSU54, 55,and 56, if one reached thethreshold values theautomated irrigation wasperformed.
The pumping rate provided10 ml/min/drip hole, whichwas measured in theautomated irrigation zone insix different drip holes.
In accordance with theorganic producer’sexperience, a minimum valueof 5% VWC for the soil wasestablished as the moisturethreshold level and 30 °C asthe temperature thresholdlevel for the automatedirrigation modes (IA3 andIA4, respectively). Initially,the scheduled irrigation (IA2)of 35 min/week was usedduring the first six weeks.After that, the scheduledirrigation was set at 35 minthree times per week. Sagecultivation finalized after 136days.
During the cultivation,several automated irrigationperiods were carried out bythe system because of the soilmoisture (IA3) or
temperature (IA4) levels, regardless of the scheduled irrigation(IA2). All data were uploaded each hour to the web server forremote supervision. For instance, data of five days are shown(Fig. 10). The first graph shows soil temperatures. The verticalbars indicate automated irrigation periods triggered bytemperature when soil temperature was above the thresholdvalue (30 °C). The second graph shows soil moistures that wereabove the threshold value (5.0% VWC), and thus the automatedirrigation was not triggered by soil moisture. Finally, the lastgraph shows the total water used by the sage with thecorresponding scheduled irrigation vertical bars for the IA2.The dots denote the automated and scheduled irrigation.
Automated irrigationtriggered by soil moisture forfour days are shown in Fig.11; when the soil moisturevalue fell below the thresholdlevel of 5.0% VWC, theirrigation system wasactivated for 35 minaccording to IA3, whereasthe soil temperature remainedbelow the threshold level.
Similarly, Fig. 12 showsautomated irrigation triggeredby soil temperature; when thetemperature was above 30 °C,the irrigation system wasactivated for 5 min accordingto IA4, whereas the soilmoisture remained above thethreshold level.
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8 IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
Fig. 11. Automated irrigation (vertical bars) triggered by the soil moisture
threshold ≤ 5% VWC.
Fig. 14. Automated irrigation systems for the experimental production of:sage (top left), thyme (top right), origanum (bottom left), and basil (bottomright) in San Jose del Cabo, Los Arados, El Pescadero, and El Comitan,respectively.
250
Fig. 12. Automated irrigation (vertical bars) triggered by the soil temperature
threshold ≥ 30 °C.
(mA
)
200
(°C
) 30c
20150
25 b 15
Tem
per
atu
re
VW
C (
%)
Cu
rre
nt20
a10
d 100
15 5
10 50 Sleep (4.47 μA)
40000 5 10 15 20 25 30 35)
3
300 Time (s)(m
200
Wat
er
100 Fig. 15. WSU current consumption in monitoring and sleep modes.0
40 60 80 100 120 14020
Day
Fig. 13. Daily mean soil temperature (a: traditional; b: automated), daily meansoil moisture (c: traditional; d: automated), and accumulated water irrigationvolumes (dotted line: traditional; solid line: automated) over the entire sagecropping season.
Water consumption with the organic producers’ traditionalirrigation procedure consisted of watering with a 2” electricalpump during 5 h three times per week for the whole cultivationperiod. Under this scheme the volume flow rate measured onsite was 10 ml/min/per drip hole, giving a total of 174 l/driphole, whilst the automated irrigation system used 14 l/drip hole.In the entire greenhouse, the sage plants presented similar freshbiomass regardless of the irrigation procedure during the wholeproduction period. The average biomass per cut was 110pounds for the traditional irrigation system corresponding to 42production beds and 30 pounds for the automated irrigationsystem corresponding to 14 beds.
The automated system was tested in the greenhouse for 136days (Fig. 13). Daily mean soil moisture and temperature are
shown, as well as theaccumulated water used forboth systems. Both meantemperatures presentedsimilar behavior for theproduction period, except forthe last 30 days, where thesoil temperature for thetraditional irrigation practice
(curve a) was lower than theautomated irrigation (curveb). The daily mean VWC forthe traditional irrigationpractice (curve c) was almostconstant >16%, whereas thatfor the automated irrigation(curve d) was below 10%. Inaddition, the accumulatedwater used are showncorresponding to 14 beds foreach irrigation system. Thetotal water requirement was341 m3 for the traditional oneand 29 m3 for the automatedone. Then, the automatedirrigation used ∼90% lesswater with respect to thetraditional irrigation practice.
Another three automatedirrigation systems (Fig. 14)have been tested along 18
months in other places in BCS, Mexico: El Pescadero (23°21.866’ N, 110° 10.099’ W), El ComitanCIBNOR (24° 7.933’N, 110° 25.416’ W), and Los Arados (24° 47.1’ N, 111°11.133’ W). In these three places, programmed irrigations (IA2) were compared with triggered irrigations (IA3 and IA4),water savings ∼60% were obtained.
For cases such as Los Arados, it was found that the signal
receiving strength was toolow and the Internetconnection could not beestablished, hence in this caseall data were stored into thesolid state memory of theWIU.
Power consumption of aWSU was measured throughcurrent oscilloscope (UNITUT81B) in the monitoring andsleep operational modes (Fig.15). Each hour, the soilmoisture
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GUTIÉRREZ et al.: AUTOMATED IRRIGATION SYSTEM USING A WSN AND GPRS MODULE 9
4.5
4.25With solar panel
(V)
Vo
ltag
e
4
3.75Without solar panel
3.502 03 04 05 06 07 08 09 10 11 1201
Day
Fig. 16. Battery charge–discharge cycle of a wireless sensor unit (WSU).
TABLE II
COMPONENTS
FOR WIU
800
) 700
2(W
/m 600
500
rad
iati
on
400
300
So
lar
200
100
002 03 04 05 06 07 08 09 10 11 12 1301
Day
Fig. 17. Solar radiation along the experiment of chargedischarge cycle of a wireless sensor unit (WSU).
TABLE I
COMPONENTS FOR WSU
and temperature data were transmitted to theWIU. Before transmitting the data, the XBeeof the WSU was powered on through thevoltage regulator that was enabled for aperiod of 20 s by the microcontroller, whichwas a long enough time for the radio modemto wake up and transmit the data. Then, thetotal average power consumption was kept at0.455 mAh. The chargedischarge cycle ofthe batteries is shown for 20 days in the
winter withthe solarpanelconnectedanddisconnected(Fig. 16)using the dataregistered bythe batteryvoltagemonitor. Thesolarradiation forthose days isshown in Fig.17. Thus, thephotovoltaicpanel and thebatteriesprovidesufficientenergy tomaintain theWSU runningfor the wholecrop seasonat almost anylatitude, duethe lowenergyconsumption.
The WIUaveragecurrentconsumptionbecause ofthe electroniccomponentswas of 80mAh inoperationalmode.
use, the importanceof the preservationof this naturalresource justify theuse of this kind ofirrigation systems.
ACKNOWLEDGMENT
The authorswould like to thankP. Luna, J. Cobos,A. Alvarez, C. Soto,M. Cordoba, and J.Mandujano for theirsupport.
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10
REFERENCES
[1]W. A. Jury and H. J. Vaux, “The emerging global watercrisis: Managing scarcity and conflict between waterusers,” Adv. Agronomy, vol. 95, pp. 1–76, Sep. 2007.
[2]X. Wang, W. Yang, A. Wheaton, N. Cooley, and B.Moran, “Efficient registration of optical and IR imagesfor automatic plant water stress assessment,” Comput.Electron. Agricult., vol. 74, no. 2, pp. 230–237, Nov.2010.
[3]G. Yuan, Y. Luo, X. Sun, and D. Tang, “Evaluation of a cropwater stress index for detecting water stress in winter wheatin the North China Plain,” Agricult. Water Manag., vol. 64,no. 1, pp. 29–40, Jan. 2004.
[4] S. B. Idso, R. D. Jackson, P. J. Pinter, Jr., R. J. Reginato, and
10. L. Hatfield, “Normalizing the stressdegreedayparameter for environmental variability,” Agricult.Meteorol., vol. 24, pp. 45–55, Jan. 1981.
[5]Y. Erdem, L. Arin, T. Erdem, S. Polat, M. Deveci, H.Okursoy, and
8.T. Gültas, “Crop water stress index for assessingirrigation scheduling of drip irrigated broccoli (Brassicaoleracea L. var. italica),” Agricult. Water Manag., vol. 98,no. 1, pp. 148–156, Dec. 2010.
[6]K. S. Nemali and M. W. Van Iersel, “An automatedsystem for controlling drought stress and irrigation inpotted plants,” Sci. Horticult., vol. 110, no. 3, pp. 292–297, Nov. 2006.
[7]S. A. O’Shaughnessy and S. R. Evett, “Canopytemperature based system effectively schedules andcontrols center pivot irrigation of cotton,” Agricult.Water Manag., vol. 97, no. 9, pp. 1310–1316, Apr. 2010.
[8]R. G. Allen, L. S. Pereira, D. Raes, and M. Smith, CropEvapotranspirationGuidelines for Computing CropWater Requirements—FAO Irrigation and DrainagePaper 56. Rome, Italy: FAO, 1998.
[9]S. L. Davis and M. D. Dukes, “Irrigation schedulingperformance by evapotranspirationbased controllers,”Agricult. Water Manag., vol. 98, no. 1, pp. 19–28, Dec.2010.
[10] K. W. Migliaccio, B. Schaffer, J. H. Crane, and F.S. Davies, “Plant response to evapotranspiration and soilwater sensor irrigation scheduling methods for papayaproduction in south Florida,” Agricult. Water Manag.,vol. 97, no. 10, pp. 1452–1460, Oct. 2010.
[11] J. M. Blonquist, Jr., S. B. Jones, and D. A.Robinson, “Precise irrigation scheduling for turfgrassusing a subsurface electromagnetic soil moisture sensor,”Agricult. Water Manag., vol. 84, nos. 1–2, pp. 153–165,Jul. 2006.
[12] O. M. Grant, M. J. Davies, H. Longbottom, and C.J. Atkinson, “Irrigation scheduling and irrigation systems:Optimising irrigation efficiency for container ornamentalshrubs,” Irrigation Sci., vol. 27, no. 2, pp. 139–153, Jan.2009.
[13] Y. Kim, R. G. Evans, and W. M. Iversen, “Remotesensing and control of an irrigation system using adistributed wireless sensor network,” IEEE Trans.Instrum. Meas., vol. 57, no. 7, pp. 1379–1387, Jul. 2008.
[14] Y. Kim and R. G. Evans, “Software design forwireless sensorbased sitespecific irrigation,” Comput.Electron. Agricult., vol. 66, no. 2, pp. 159–165, May2009.
[15] D. K. Fisher and H. A. Kebede, “A lowcostmicrocontrollerbased system to monitor croptemperature and water status,” Comput. Electron.Agricult., vol. 74, no. 1, pp. 168–173, Oct. 2010.
[16] Y. Kim, J. D. Jabro, and R. G. Evans, “Wireless
lysimeters for real time online soil water monitoring,” Irrigation Sci., vol. 29, no. 5,pp. 423–430, Sep. 2011.
[17] O. Mirabella and M.Brischetto, “A hybridwired/wireless networkinginfrastructure for greenhousemanagement,” IEEE Trans.Instrum. Meas., vol. 60, no.2, pp. 398–407, Feb. 2011.
[18] I. F. Akyildiz, W. Su,Y. Sankarasubramaniam, andE. Cayirci, “A survey onsensor networks,” IEEECommun. Mag., vol. 40, no.8, pp. 104–112, Aug. 2002.
[19] J. Yick, B. Mukherjee,and D. Ghosal, “Wirelesssensor network survey,”Comput. Netw., vol. 52, no.12, pp. 2292–2330, Aug.2008.
[20] M. Winkler, K.D.Tuchs, K. Hughes, and G.Barclay, “Theoretical andpractical aspects of militarywireless sensor networks,” J.Telecommun. Inf. Technol.,vol. 2, pp. 37–45, Apr./Jun.2008.
[21] M. P. Durisic, Z. Tafa,G. Dimic, and V.Milutinovic, “A survey ofmilitary applications ofwireless sensor networks,” inProc. MECO, Jun. 2012, pp.196–199.
[22] M. C. RodríguezSánchez, S. Borromeo, and J.A. HernándezTamames,“Wireless sensor networksfor conservation andmonitoring cultural assets,”IEEE Sensors J., vol. 11, no.6, pp. 1382–1389, Jun. 2011.
[23] G. López, V. Custodio,and J. I. Moreno, “LOBIN:Etextile and wirelesssensornetworkbasedplatform for healthcaremonitoring in future hospitalenvironments,” IEEE Trans.Inf. Technol. Biomed., vol.14, no. 6, pp. 1446–1458,Nov. 2010.
IEEE TRANSACTIONS ONINSTRUMENTATION AND
MEASUREMENT
[24] J. M. Corchado, J. Bajo, D. I.Tapia, and A. Abraham,“Using heterogeneouswireless sensor networks in atelemonitoring system forhealthcare,” IEEE Trans. Inf.Technol. Biomed., vol. 14,no. 2,pp. 234–240, Mar. 2010.
[25] G. X. Lee, K. S. Low,and T. Taher, “Unrestrainedmeasurement of arm motionbased on a wearable wirelesssensor network,” IEEETrans. Instrum. Meas., vol.59, no. 5, pp. 1309–1317,May 2010.
[26] D.M. Han and J.H.Lim, “Smart home energymanagement system usingIEEE 802.15.4 and ZigBee,”IEEE Trans. Consum.Electron., vol. 56, no. 3, pp.1403–1410, Aug. 2010.
[27] C. Gomez and J.Paradells, “Wireless homeautomation networks: Asurvey of architectures andtechnologies,” IEEECommun. Mag., vol. 48, no.6, pp. 92–101, Jun. 2010.
[28] M. Bertocco, G.Gamba, A. Sona, and S.Vitturi, “Experimentalcharacterization of wirelesssensor networks forindustrial applications,”IEEE Trans. Instrum. Meas.,vol. 57, no. 8, pp. 1537–1546, Aug. 2008.
[29] V. C. Gungor and G. P.Hancke, “Industrial wirelesssensor networks: Challenges,design principles, andtechnical approaches,” IEEETrans. Ind. Electron., vol.56, no. 10, pp. 4258–4265,Oct. 2009.
[30] L. Hou and N. W.Bergmann, “Novel industrialwireless sensor networks formachine conditionmonitoring and faultdiagnosis,” IEEE Trans.Instrum. Meas., vol. 61, no.10, pp. 2787–2798, Oct.2012.
[31] A. Carullo, S.Corbellini, M. Parvis, and A.Vallan, “A wireless sensornetwork for coldchainmonitoring,” IEEE Trans.Instrum. Meas., vol. 58, no.5, pp. 1405–1411, May 2009.
[32] A. Araujo, J. GarciaPalacios, J. Blesa, F. Tirado,E. Romero, A. Samartin, andO. NietoTaladriz, “Wirelessmeasurement system forstructural health monitoringwith high timesynchronization accuracy,”IEEE Trans. Instrum. Meas.,
vol. 61, no. 3, pp. 801–810, Mar. 2012.
[33] P. Corke, T. Wark, R. Jurdak, H. Wen, P. Valencia,and D. Moore, “Environmental wireless sensornetworks,” Proc. IEEE, vol. 98, no. 11,
42. 1903–1917, Nov. 2010.
[34] L. M. Oliveira and J. J. Rodrigues, “Wireless sensornetworks: A survey on environmental monitoring,” J.Commun., vol. 6, no. 2, pp. 143–151, Apr. 2011.
[35] H.C. Lee, Y.M. Fang, B.J. Lee, and C.T. King,“The tube: A rapidly deployable wireless sensor platformfor supervising pollution of emergency work,” IEEETrans. Instrum. Meas., vol. 61, no. 10,
42. 2776–2786, Oct. 2012.
[36] H.C. Lee, A. Banerjee, Y.M. Fang, B.J. Lee, andC.T. King, “Design of a multifunctional wireless sensorfor insitu monitoring of debris flows,” IEEE Trans.Instrum. Meas., vol. 59, no. 11, pp. 2958–2967, Nov.2010.
[37] N. Wang, N. Zhang, and M. Wang, “Wirelesssensors in agriculture and food industry—Recentdevelopment and future perspective,” Comput. Electron.Agricult., vol. 50, no. 1, pp. 1–14, Jan. 2006.
[38] D. D. Chaudhary, S. P. Nayse, and L. M.Waghmare, “Application of wireless sensor networks forgreen house parameters control in precision agriculture,”Int. J. Wireless Mobile Netw., vol. 3, no. 1, pp. 140–149,Feb. 2011.
[39] P. Mariño, F. P. Fontan, M. A. Dominguez, and S.
Otero, “An experimental adhoc WSN for theinstrumentation of biologicalmodels,” IEEE Trans.Instrum. Meas., vol. 59, no.11, pp. 2936–2948, Nov.2010.
[40] M. Johnson, M. Healy,P. van de Ven, M. J. Hayes,J. Nelson, T. Newe, and E.Lewis, “A comparativereview of wireless sensornetwork mote technologies,”in Proc. IEEE Sensors, Oct.2009, pp. 1439–1442.
[41] J. S. Lee, Y. W. Su,and C. C. Shen, “Acomparative study ofwireless protocols:Bluetooth, UWB, ZigBee,and WiFi,” in Proc. IEEE33rd Annu. Conf. IECON,Nov. 2007, pp. 46–51.
[42] M. R. Frankowiak, R. I.Grosvenor, and P. W.Prickett, “A review of theevolution of microcontrollerbased machine and processmonitoring,” Int. J. Mach.Tool Manuf., vol. 45, nos. 4–5, pp. 573–582, Apr. 2005.
[43] C. Kompis and P.Sureka, “Power managementtechnologies to enableremote and wirelesssensing,” ESP KTN,Teddington, U.K., Tech.Rep., May 2010.
[44] M. T. Penella and M.Gasulla, “Runtime extensionof lowpower wireless sensornodes using hybridstorageunits,” IEEE Trans. Instrum.Meas., vol. 59, no. 4, pp.857–865, Apr. 2010.
[45] W. K. G. Seah, Z. A.Eu, and H.P. Tan, “Wirelesssensor networks powered byambient energy harvesting(WSNHEAP)—Survey andchallenges,” in Proc. 1st Int.Conf. Wireless VITAE, May2009, pp. 1–5.
[46] Y. K. Tan and S. K.Panda, “Selfautonomouswireless sensor nodes withwind energy harvesting forremote sensing of winddriven wildfire spread,”IEEE Trans. Instrum. Meas.,vol. 60, no. 4, pp. 1367–1377, Apr. 2011.
This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination.
GUTIÉRREZ et al.: AUTOMATED IRRIGATION SYSTEM USING A WSN AND GPRS MODULE
[47] E. Sardini and M. Serpelloni, “Selfpowered wireless sensor for air temperature and velocity measurements with energy harvesting capability,”IEEE Trans. Instrum. Meas., vol. 60, no. 5, pp. 1838–1844, May 2011.
[48] I. Marin, E. Arceredillo, A. Zuloaga, and“Wireless sensor networks: A survey on ultralow poweraware design,” in Proc. WASET, vol. 8.
42. 1–6.
[49] S. Kolli and M. Zawodniok, “Energyefficient multikey security scheme forwireless sensor network,” in Proc. IEEE 34thConf. LCN, Oct. 2009,
42. 937–944.
[50] J. Lin, W. Xiao, F. L. Lewis, and L.Xie, “Energyefficient distributed adaptivemultisensor scheduling for target tracking inwireless sensor networks,” IEEE Trans.Instrum. Meas., vol. 58, no. 6, pp. 1886–1896, Jun. 2009.
[51] P. Györke and B. Pataki, “Energyaware measurement scheduling in WSNsused in AAL applications,” IEEE Trans.Instrum. Meas., vol. 62, no. 5, pp. 1318–1325, May 2013.
[52] R. Yan, H. Sun, and Y. Qian,“Energyaware sensor node design with itsapplication in wireless sensor networks,”IEEE Trans. Instrum. Meas., vol. 62, no. 5,pp. 1183–1191, May 2013.
[53] Q. Wang, W. Yan, and Y. Shen, “Nperson card game approach for solving SETKCOVER problem in wireless sensornetworks,” IEEE Trans. Instrum. Meas.,vol. 61, no. 5, pp. 1522–1535, May 2012.
[54] F. Pianegiani, M. Hu, A. Boni, and D.Petri, “Energyefficient signal classificationin ad hoc wireless sensor networks,” IEEETrans. Instrum. Meas., vol. 57, no. 1, pp.190–196, Jan. 2008.
[55] C. Alippi, G. Anastasi, D. Francesco,and M. Roveri, “An adaptive samplingalgorithm for effective energy managementin wireless sensor networks with energyhungry sensors,” IEEE Trans. Instrum.Meas., vol. 59, no. 2, pp. 335–344, Feb.2010.
[56] P. Suriyachai, U. Roedig, and A.Scott, “A survey of MAC protocols formissioncritical applications in wirelesssensor networks,” Commun. Surveys Tuts.,vol. 14, no. 2, pp. 240–264, Apr./Jun. 2012.
[57] Wireless Medium Access Control(MAC) and Physical Layer (PHY)Specifications: HigherSpeed PhysicalLayer Extension in the 2.4 GHz Band, IEEEStandard 802.11b, 1999.
[58] Wireless Medium Access Control (MAC)and Physical Layer (PHY) Specificationsfor Wireless Personal Area Networks(WPANs), IEEE Standard 802.15.1, 2002.
[59] Wireless Medium Access Control(MAC) and Physical Layer (PHY)
Specifications:High RateWireless PersonalArea Networks(WPANs), IEEE Standard 802.15.3, 2003.
[60] Wireless MediumAccess Control(MAC) andPhysical Layer(PHY)Specifications forLowRateWireless PersonalArea Networks(LRWPANs),IEEE Standard802.15.4, 2003.
[61] Request forComments (RFC)4944Transmission ofIPv6 Packets overIEEE 802.15.4Networks, InternetEng. Task Force,Orlando, FL,USA, 2007.
[62] J. E. Higueraand J. Polo, “IEEE1451 standard in6LoWPAN sensornetworks using acompact physicallayer transducerelectronicdatasheet,” IEEETrans. Instrum.Meas., vol. 60, no.8, pp. 2751–2758,Aug. 2011.
[63] IndustrialCommunicationNetworkFieldbusSpecificationsWirelessHARTCommunicationNetwork andCommunicationProfile, Edition1.0, StandardIEC/PAS 62591,2009.
[64] WirelessSystems forIndustrialAutomation:Process Controland RelatedApplications,Standard ISA100.11a2009,2009.
[65] P. Baronti, P.Pillai, V. W. C.Chook, S. Chessa,A. Gotta, and Y.F. Hu, “Wirelesssensor networks:A survey on thestate of the art andthe 802.15.4 andZigBeestandards,”Comput.Commun., vol. 30,
no.7,pp.1655–1695,May 2007.
[66]W.
Guo,W.M.Healy,and Z.MengChu,“Impacts of2.4GHz IS
M band interference on IEEE 802.15.4wireless sensor network reliability inbuildings,” IEEE Trans. Instrum. Meas.,vol. 61, no. 9, pp. 2533–2544, Sep. 2012.
[67] N. Baker, “ZigBee and Bluetoothstrengths and weaknesses for industrialapplications,” Comput. Control Eng. J., vol.16, no. 2, pp. 20–25, Apr./May 2005.
11
Joaquín Gutiérrez received thePh.D. degree in artificial intelligencefrom the Instituto Tecnológico y deEstudios Superiores de Monterrey,Monterrey, México, in 2004.
He is a Researcher with the Centrode Investigaciones Biológicas delNoroeste, S.C., La Paz, BCS, México.His current research interests includethe development and experimentalvalidation of robotic systems forbiological research applications.
Juan Francisco VillaMedinareceived the B.T. degree incomputational engineering fromInstituto Tecnológico de La Paz,México, in 2008.
He is a Technician with the Centrode Investigaciones Biológicas delNoroeste, S.C., La Paz, BCS, Mexico.His current research interests includethe development of engineeringsystems.
Alejandra NietoGaribay receivedthe Ph.D. degree in biology with amajor in ecology from the CentroUniversitario de Ciencias Biológicasy Agropecuarias, Universidad de
Guadalajara,Guadalajara, México, in 2006.
She is aResearcher with theCentro de InvestigacionesBiológicas delNoroeste, S.C., LaPaz, BCS, México,in the AgricultureProgram. Her current researchinterests include thedevelopment andexperimentalvalidation ofagriculturaltechnology in semiarid environment.
Miguel ÁngelPortaGándarareceived the Ph.D.degree inengineering fromthe UniversidadNacional Autónomade México, MéxicoCity, México, in1997.
He is aResearcher with theCentro deInvestigacionesBiológicas delNoroeste, S.C., LaPaz, BCS, Mexico.His current researchinterests include thedevelopment ofengineeringsystems forbiological researchapplications.