Deployment Strategies of Soil Monitoring WSN for Precision Agriculture Irrigation Scheduling in Rural Areas
<p>Proposed soil monitoring node for scenarios 1 and 2.</p> "> Figure 2
<p>Architecture.</p> "> Figure 3
<p>Flow chart of the Data Center.</p> "> Figure 4
<p>Simulation of an irrigation schedule for an orange field in Murcia.</p> "> Figure 5
<p>Simulation of an irrigation schedule for an orange field in Gandía.</p> "> Figure 6
<p>(<b>a</b>) Grass field. (<b>b</b>) Thicker field. (<b>c</b>) Orange field.</p> "> Figure 7
<p>Placement of the node inside the box.</p> "> Figure 8
<p>(<b>a</b>) Layout of the measures. (<b>b</b>) Satellite image of the fields.</p> "> Figure 9
<p>RSSI in grasslands.</p> "> Figure 10
<p>RSSI in scrubs.</p> "> Figure 11
<p>RSSI in Orange fields.</p> "> Figure 12
<p>RSSI in all fields.</p> "> Figure 13
<p>Model of RSSI in (<b>a</b>) grasslands, (<b>b</b>) scrubs, (<b>c</b>) orange fields at 0°, and (<b>d</b>) orange fields at 15°.</p> "> Figure 14
<p>Maximum distance for desired Prx.</p> "> Figure 15
<p>RSSI for on-ground receiver and different configurations for the emitter.</p> "> Figure 16
<p>RSSI for near-ground receiver and different configurations for the emitter.</p> "> Figure 17
<p>RSSI for above-ground receiver and different configurations for the emitter.</p> "> Figure 18
<p>Model of RSSI in the orange field with emitter (<b>a</b>) on the ground (<b>b</b>) at 50 cm of height (<b>c</b>) at 1 m of height.</p> "> Figure 19
<p>Maximum distance for desired Prx at on-ground, near-ground, and above-ground deployments.</p> ">
Abstract
:1. Introduction
- A soil monitoring proposal including an algorithm to determine the irrigation needs based on FAO recommendations and the sensed data.
- Different deployment strategies for low-cost soil monitoring nodes have been tested on real environments for three different vegetation types: orange orchards, scrublands, and grasslands.
- Finally, the key aspects of deployments of soil monitoring nodes and the results obtained from the performed tests have been discussed.
2. Related Work
3. Materials and Methods
3.1. Soil Monitoring Background
3.2. Architecture Description
3.3. Proposed Algorithm
Algorithm 1. Irrigation Algorithm. | |
1 | Variable initialization |
2 | User parameter initialization |
3 | ETo calculation |
4 | Determination of the Crop Stage |
5 | If Water stress then |
6 | Calculate irrigation adjustment due to water stress |
7 | end if |
8 | If High salinity levels then |
9 | Calculate irrigation adjustment due to salinity |
10 | end if |
11 | If Precipitation then |
12 | Determine the precipitation amount |
13 | Determine the hour of the precipitation |
14 | Calculate irrigation adjustment due to precipitation |
15 | end if |
16 | Calculate ETc |
17 | Calculate Irrigation requirements of the crop |
18 | End. |
3.4. Testbed Description
4. Results
4.1. Scenario 1: On-Ground Deployment with Different Types of Vegetation
4.2. Scenario 2: On-Ground, Near-Ground, and Above-Ground Deployments for Orange Tree Monitoring
5. Discussion and Challenges
Limitations of This Study
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Ref | Environments | Heights | Frequency | Transmitter | Receiver |
---|---|---|---|---|---|
Jose Antonio Gay-Fernández et al. [21] | Forests, scrublands, and grasslands | 0.9, 1.2, and 1.6 m | 2.4, 3.5, and 5.5 GHz | Rhode-Schwarz SMR-40 signal generator and an Electronics EM 6865 wideband antenna | Robde-Schwarz FSH-6 spectrum analyzer |
Muhammad A. et al. [20] | Urban areas, rural areas, forests, and plantations | - | 2.4 GHz | - | - |
Hairani Maisarah Rahim et al. [22] | Tropical vegetation foliage | 2 m | 2–18 GHz and 26.5–40 GHz | Anritsu MG3694C Signal Generator | Spectrum Master MS2730T |
J. Acuña et al. [23] | Shrubs | 1.25 m | 2.4 and 5.8 GHz | Rohde & Schwarz radio signal generator SMR-40 | Rhode & Schwarz FSP-40 spectrum analyzer |
Leire Azpilicueta et al. [24] | Park | 1 m | 2.4 GHz | Zigbee mote | Agilent N9912 Field Fox portable spectrum analyzer |
Jürgen Richter et al. [25] | Trees | 5–17 m | 1–60 GHz | - | - |
Nick Savage et al. [28] | Trees | 2.5–7.5 m | 1.3, 2, and 11.6 GHz | Channel sounder | Channel sounder |
John Thelen et al. [29] | Potato crop | 0 m | 433 MHz | Mica2Dot | Mica2 with MIB510 programming board and an antenna with an 11.7 dB gain |
B. Dhanavanthan et al. [34] | Cornfields and coconut gardens. | 2 cm, 15 cm, and 1 m | 2.4 GHz | Agilent N5182A Vector Signal Generator | Agilent N9010A Vector Signal Analyzer |
Andrew Szajna et al. [35] | Sports facility and a forested area covered by snow. | 0–130.8 cm | 2.45 GHz | National Instruments PXI-5670 | National Instruments PXI-5690 low noise preamplifier paired with National Instruments PXI-5660 RF vector signal analyzer. |
Daihua Wang et al. [36] | A plaza, a sidewalk, and a grassland. | 3 cm, 1 m | 2.4 GHz | RF transceiver working at 2.4GHz | Agilent N9912A spectrum analyzer |
Weisheng Tang et al. [37] | Concrete road, flat grass, and undulating grass. | 5 cm, 50 cm, and 1 m | 470 MHz | Silicon Labs Si4432 radio frequency chip | MSP430F5438 as the Microprogramed Control Unit (MCU) chip |
Seun Sangodoyin et al. [38] | Rural flat and hilly terrains. | 10 cm, 20 cm, 50 cm, and 2 m | 3–10 GHz | Tektronix AWG 7122c waveform generator | Agilent DSA91304A Digital Sampling Oscilloscope |
Amir Torabi et al. [39] | Ground plain, yard, and grass park. | 13 cm | 315 MHz, 915 MHz, 2.4 GHz | - | - |
Daniel P. Luciani et al. [40] | Concrete, grass field and hallway. | 15 cm, 30 cm, and 1 m | 2.48 GHz | STMicroelectronics STM32W-RFCKIT | Laptop |
Hicham Klaina et al. [41] | Soil, short and tall grass fields | 20 and 40 cm | 868 MHz, 2.4 GHz, and 5.8 GHz | ZigBee nodes | ZigBee nodes |
Peio Lopez-Iturri et al. [42] | Oak and pine tree fields. | 1, 2, and 3 m | 2.4 GHz | - | - |
D. L. Ndzi et al. [43] | Mango and palm plantations. | 1.3, 1.7, 2.2, and 2.6 m | 0.4–7.2 GHz | Agilent E8267D signal generator | Agilent E4405B spectrum analyzer |
Jaime Lloret et al. [44] | Rural and forest areas. | 3 m | 2.412–2.472 GHz | wireless multisensors and wireless IP cameras | 802.11g access points |
Our testbed | Orange field, scrubland, and grassland | 0, 0.5, 1 m | 2.4 GHz | ESP 32 Doit devkit v1 | ESP 32 Doit devkit v1 |
Fixed Variables | Variables Set by the User |
Elevation above sea level | Height of the tree |
Date | Selection of soil type |
Latitude | Time period for irrigation calculation |
Height of wind speed measurement | Selection of Single Coefficient Approach or Dual Coefficient Approach for ETc calculation |
Variables Obtained from the Monitored Data | |
Maximum air temperature of the day | Water salinity |
Minimum air temperature of the day | Soil conductivity |
Maximum relative humidity of the day | Soil humidity |
Minimum relative humidity of the day | Soil temperature |
Hours of sunlight of the day | Mean temperature of the actual month |
Wind speed | Mean temperature of the previous month |
Precipitation amount | Estimated mean temperature of the following month |
Hour of the precipitation |
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García, L.; Parra, L.; Jimenez, J.M.; Parra, M.; Lloret, J.; Mauri, P.V.; Lorenz, P. Deployment Strategies of Soil Monitoring WSN for Precision Agriculture Irrigation Scheduling in Rural Areas. Sensors 2021, 21, 1693. https://doi.org/10.3390/s21051693
García L, Parra L, Jimenez JM, Parra M, Lloret J, Mauri PV, Lorenz P. Deployment Strategies of Soil Monitoring WSN for Precision Agriculture Irrigation Scheduling in Rural Areas. Sensors. 2021; 21(5):1693. https://doi.org/10.3390/s21051693
Chicago/Turabian StyleGarcía, Laura, Lorena Parra, Jose M. Jimenez, Mar Parra, Jaime Lloret, Pedro V. Mauri, and Pascal Lorenz. 2021. "Deployment Strategies of Soil Monitoring WSN for Precision Agriculture Irrigation Scheduling in Rural Areas" Sensors 21, no. 5: 1693. https://doi.org/10.3390/s21051693
APA StyleGarcía, L., Parra, L., Jimenez, J. M., Parra, M., Lloret, J., Mauri, P. V., & Lorenz, P. (2021). Deployment Strategies of Soil Monitoring WSN for Precision Agriculture Irrigation Scheduling in Rural Areas. Sensors, 21(5), 1693. https://doi.org/10.3390/s21051693