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This study seeks to develop an automated solar-powered irrigation system. This will provide a cost-effective solution to the traditional irrigation method. This project is aimed at designing a system that harnesses solar energy for smart irrigation and allows for more efficient way to conserve water on the farmland. The system developed is portable and is designed to be adaptable to existing water system. The system incorporates wireless communication technology established using NRF module. For easy operations, the system can be controlled via an Android app-enabled with Bluetooth network. The user experience allows selection of either manual control for scheduled irrigation or automatic control using wireless sensors.
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Smart-Solar Irrigation System (SMIS) for Sustainable
Agriculture
Olusola Abayomi-Alli 1, Modupe Odusami1, Daniel Ojinaka1, Olamilekan
Shobayo1, Sanjay Misra1 ,Robertas Damasevicius2, Rytis Maskeliunas2
1 Department of Electrical and Information Engineering, Covenant University, Ota, Nigeria.
2Kanus University of Technology, Kaunas, Lithuania
{olusola.abayomi-alli, modupe.odusami, olamilekan.shobayo,
sanjay.misra}@covenantuniversity.edu.ng, {robertas.damasevicius,rytis.maskeliunas}@ktu.lt
Abstract. This study seeks to develop an automated solar-powered irrigation
system. This will provide a cost-effective solution to the traditional irrigation
method. This project is aimed at designing a system that harnesses solar energy
for smart irrigation and allows for more efficient way to conserve water on the
farmland. The system developed is portable and is designed to be adaptable to
existing water system. The system incorporates wireless communication
technology established using NRF module. For easy operations, the system can
be controlled via an Android app-enabled with Bluetooth network. The user
experience allows selection of either manual control for scheduled irrigation or
automatic control using wireless sensors.
1 Introduction
Agriculture is the foundation of Africa's economy and the major source of food in any
nation, therefore, improving this sector plays a crucial role in building sustainable
systems and growing any economy. Around 70% of Africans are rural dwellers and are
mostly of the poor populace which depends majorly on agribusiness to maintain
sustainability and employment. Agribusiness is the principal wellspring for sustenance
for 60-70% of the populace in sub-Sahara Africa. This sector is confronted with several
difficulties making it hard to meet its main role of nourishing the country [1].
The increasing growth of the global population with over 7 billion individuals
and an estimated increase of 9.6 billion by the year 2050 [2] shows that there is a need
to double generation and production within a discreetly brief time. This will be essential
in achieving the Sustainable Development Goal (SDG) 1and 2, “NO POVERTY” and
“ZERO HUNGER”. There is a need to change the traditional agricultural practice in
order to meet the rising demands of food security thus contributing effectively to the
reduction of poverty and hunger in the economy.
Recently, 90% of food production in sub-Saharan comes from small-scale
farmers, cultivating on an exact piece of the 70% of arable land accessible, depending
on rainfall as opposed to irrigation [4]. Agriculture practice in Africa is faced with
numerous challenges some of which includes:
1. Poor Power Supply to Farms
2. Poor Irrigation, Fertilization and Drainage System
3. Poor Transportation Network
4. Limited access to funds
5. Poor Farm Mechanization
These challenges have made agricultural practice frustrating for the farmer and also
contributed to the poor turn-out in large-scale farming. This study, however, focuses on
automated irrigation system with a clean and affordable power supply which is a major
factor associated with large-scale farming in Africa.
Automating Irrigation system is an intelligent or artificial application of water
for effective agriculture and cultivation production. This condition is essential for
insufficient rainfall with its focus on supplying satisfactory quantity of water at the right
time for improving growth and development of farm produce. In agricultural irrigation,
the effects of the applied amount of water, the timing of irrigation and water utilization
are particularly important. With the increasing water requirements in irrigation systems,
there is a need for an automated water system with scheduling features to save about
80% of the water thus, improving water efficiency and agricultural productivity in
general particularly under conditions of water scarcity [5]. The rest of the paper is
divided into sections where: Section 2 gave a comprehensive description of the
literature review and Section 3 gave a detailed methodology. The system
implementation and testing is discussed in Section 4 and the conclusion and future
recommendation is summarized in Section 5.
2 Literature Review
The major limitations in sustainable agricultural development and advancement in
the sub-Saharan include the crude way in farm practices and production, low efficiency
and poor technological adaptation. Thus, current headway is the need for a system that
makes the agricultural process simpler and stress-free for farmers thereby increasing
the annual/seasonal production through creating an agro-driven environment. Several
works has been done by researchers globally, in developing a smart irrigation controller
system.
2.1 Related Work
Various methodologies have been adapted to implement most of the smart irrigation
systems over the years. This technology includes the use of wireless communications,
weighing lysimeter technique, SCADA systems for supervisory and Artificial Neural
Network (ANN).
2.2 Irrigation System based on Wireless Communication Technologies
This section describes the various types of wireless communication protocols and its
standards that are being adopted in agriculture varying from Zigbee wireless protocol,
Bluetooth, Wifi, GPRS, etc. The fast advancement of wireless communication and
embedded micro-sensing electromechanical systems (MEMS) technologies has made
wireless sensor networks (WSN) possible.
[6] designed an autonomous solar-powered irrigation system using GPRS, Zigbee,
and Radio connectivity. The system designed to consist of two major units; the wireless
sensor units and the wireless information unit linked together using radio transceivers.
The wireless sensor is configured using ZigBee technology and firms the sensors, a
microcontroller, and power sources. Several wireless sensors can be utilized in-field to
configure a distributed sensor network for the automated irrigation system. [7]
presented a soil moisture sensor to estimate the soil volumetric water content. The
sensor is based on the soils dielectric constant also known as soil bulk permittivity. In
his design, the temperature of the soil was measured using LM35 wrapped-in. The
temperature and the soil moisture level measured are read using an Arduino Uno and
the analog values are converted appropriately and the result is displayed on the LCD
while it is also sent to the control room located few distances away from the farmland
sent wirelessly using Bluetooth technology.
[8] proposed an automated wireless watering system which has a user-friendly
interface to notify with information regarding the system status. The system was
designed to enable the user with the option of operating it manually or automatic and
also provides a data history of the activities of the system. [9] proposed a wireless
sensor technology to automate the Indian agricultural systems. The proposed system
was able to control several data such as Humidity, Soil Moisture, and Soil pH using the
wireless sensor nodes which serve as inputs to the Peripheral Interface Controller (PIC).
These data are continuously monitored by the controller and a GSM modem was
incorporated to send SMS to the farmer. The summary of the cons and pros of wireless
communication technology is depicted in Table 1.
Table 1. Pros and cons of a wireless communication technology.
Wireless communication technologies
Pros
Cons
1. Enables remote monitoring and control
by User or farmer.
This is a major barrier to implementing
IOT enabled irrigation because it tends to
increase the cost by acquiring internet
services
2. Enables collecting, storing and sharing
of data through web servers for
agricultural improvements.
3.Mobile Application and GSM
communication are easily integrated with
the system and enable instant notification
of system operations.
2.3 Irrigation System based on Weighing Lysimeter Technique.
A lysimeter is a device used in agronomy to measure the volume of incoming water
(rainfall and irrigation) and water coming out (drainage, evapotranspiration) of a
container containing an isolated mass of soil [10]. [10] designed an irrigation system
based on a weighing lysimeter for potted plants. The system consist of a triangular
platform that supports the pot rests on three load cells located at their vertices and are
used to measure the weight. In order to measure the irrigation water, a high-precision
low-range flow meter was required. [5] developed a prototype smart watering system
for small potted plants. The system consists of a microcontroller (ATmega328),
moisture and temperature sensors, water pump and the servo engine. The pros and cons
of the lysimeter techniques are represented in Table 2.
Table 2. Pros and Cons of weighing Lysimeter technique.
Weighing Lysimeter
Pros
1. Accurate crop evapotranspiration
data is gathered.
2. Efficient in irrigation timing and
drainage use.
Limited to potted crops only and requires
a lot of precision
Implementation on large scale farming
is difficult
2.3 Irrigation System based on SCADA software
Supervisory Control and Data Acquisition (SCADA) is a PC framework for the
gathering and examination of real-time information [11]. This utilizes a focal
framework that examines and controls the entire configuration of other systems, which
is stretched over distances of long range. [11] developed and implemented a solar-
powered irrigation system using SCADA software. The parameters used are the soil
moisture condition, suns position, water level condition, etc. The pros and cons are
listed in Table 3.
Table 3. Pros and Cons of SCADA softwares.
SCADA
Pros
Cons
1. SCADA systems are good
software’s for supervision and
monitoring and processes real-time
data.
SCADA systems are expensive and
difficult to implement on a small
scale farms.
2.4 Irrigation System based on Artificial Neural Network.
Recently, “Machine to Machine (M2M) and ANN” communications is getting more
attention, the capacity of information transfer among gadgets to servers or Cloud
through core networks enables ANN systems to learn fast. ANN control systems can
be utilized to accomplish the definitive point of water management on farmland [12].
[13] proposed the application of ANN controllers using MATLAB for irrigation
purposes. The parameter used in the proposed study is based on natural temperature
and water content in the soil. The experiment was demonstrated using environmental
conditions, evapotranspiration and the kind of crop. However, the measure of water
required for the water system is assessed and related outcomes were evaluated. [14]
developed an intelligent IOT based Automated Irrigation system where sensor
information relating to soil dampness and temperature gathered and likewise, kNN
arrangement machine learning calculation sent for analyzing the sensor information for
expectation towards flooding the soil with water. This is a completely automated with
devices communicating with the other and apply the intelligence in irrigation. This has
been created utilizing minimal cost embedded systems like Arduino Uno, Raspberry
Pi3.
Considering the existing work on automating irrigation system there are needs for a
more enhance Agric-support system with efficient power, cost-effective and functional
system in rural areas and beyond. Table 4 shows the overview of related study based
on automatic irrigation system.
3 Design Methodology
This section gives a detailed description of the proposed system design and its
specification. Considering the cost of manpower, cost of powering a pumping machine,
and cost of effectively monitoring of an irrigation process within a large expanse of
farmland, there is a need for a smart irrigation system. The Solar Smart Irrigation
System (SMIS) is designed to specific requirements. These requirements are
categorized as follows;
1. Hardware requirements
2. Software requirements
3.1 Hardware Requirement
This stage is divided into two main parts namely the central control unit and the sensor
units. The central control unit act as the brain of the entire system and its major role is
to coordinate and manage the activities of the different parts of the system which
include the solar panel, battery, microcontroller (ATmega328), solenoid valve and the
float channels. While the sensory units consist of the soil moisture sensor for gathering
data about the soil moisture content and send feedback to the central control unit
automatically. Wireless communication was established between the central control
unit and the sensory part using near radio frequency (NRF4L). Each of the sensor unit
and the central control unit is designed to have an independent solar power supply built
with the system. The block diagram of the system is shown in Figure 1.
Table 4. Overview of Related Works.
AUTHOR
POWER
MICRO-CONTOLLER
OPERA
TION
MODE
SENSOR TYPES
AC
DC
Solar DC
Arduino
Other
Zigbee
GSM
GPRS
SCADA
Webserver
Automatic
Manual
Moisture
Sensors
Humidity
Sensor
PH Sensors
Temperatu
re Sensors
[15]
*
*
*
*
*
*
*
[16]
*
*
*
*
*
*
*
*
*
[5]
*
*
*
*
*
[11]
*
*
*
*
*
*
[17]
*
*
*
*
*
[18]
*
*
*
*
*
*
*
[19]
*
*
*
*
[20]
*
*
*
*
[21]
*
*
*
*
[22]
*
*
*
*
[10]
*
*
*
*
*
[7]
*
*
*
*
*
*
In a bid to design a portable and compact irrigation system, the design of the water flow
was considered to be built and housed within the main controller. The flow of water is
channeled from the reservoir or storage tank to the inlet of the controller where the
actuators are placed. This system is designed to have two outlets for each sensory unit
as shown in Figure 2.
Fig 1. The Architecture of the proposed Solar Smart Irrigation System (SMIS)
Fig 2. Schematics Piping Channels of the proposed system
Reservoir Supply Solenoid
valve
Distribution
Solenoid valves
PV Generator
RTCC
NRF
Mobile
Application
Charge
Controller
Battery
Voltage
Regulator
Microcontroll
er
Bluetooth Module
PV Generator
Charge
Controller
Battery
Voltage
Regulator
Microcontroller
Wireless
Moisture
Sensors
NRF
Valve
s
RESERVOIR
Valve
s
3.2 Software Requirement
The SMIS was designed to enable the user operates the system manually from a control
room using Bluetooth technology. The mobile application is built to function on
Android Operating System. The choice of Bluetooth network as a communication link
between the mobile application and the hardware device is based on the power
consumption, cheaper and less complexity when compared with ZigBee or Wi-Fi
technology. The flexibility of the proposed system allows users to decide the mode of
the system operation and it, however, allows interoperability of mode operations from
automatic or manual. The flowchart diagram for the proposed SMIS system is depicted
in Figure 3 and the algorithm for the mobile application is shown in Algorithm 1.
USER START
IS OPERATION
MODE AUTO? SET SENSORS
ON STANBY
WEATHER
FORCAST
ACTIVATE AUTO
SENSOR
SET MOISTURE
REQUIREMENT(S)
COLLECT SENSOR
DATA (a)
IS( a)<(s)
OPEN VALVE
UNTIL (a)=(S)
CLOSE VALVE
END
SET TIME OF
SCHEDULED
IRRIGATION
SET
COUNTER=0
SET
TIME=COUNTER
+1
IS SET
TIME=REAL TIME
OPEN VALVE
REPEAT UNTIL
(SET TIME>1MIN)
CLOSE VALVE
COUNTER=COUN
TER +1
DISPLAY SET
TIME OF
IRRIGATION
GET REAL
TIME FROM
RTCC
STORE DATA
Date, Time , Schedule
time,time on, time off
NO
YES
NO
YES
YES
Fig 3. The flow diagram for the Proposed SMIS system
Algorithm 1. Algorithm for the Mobile Application
4 System Implementation and Testing
This section described the implementation of the system with discussion of required
equipment used in effectively developing the system and the distinctive programming
used in implementing the objectives of the system. In addition, different parts of the
system were examined and tested in order to ensure that the proposed system plays up
to its required capacity.
Input { procedure (mode): auto, manual sensor data ‘data’, soil
moisture threshold s, current time tC, time on tO, set time tS}
Output: {open valve VO, closed valve VC }
Start
Step 1: if (mode == auto)
{
activate_sensory_unit()
while True: # run in a loop
data = sensor_data();
Step 2: if (data < s)
{
if (VC == True)
{
open_valve()
continue;
}
Step 3: else if (VO == True)
{
continue
else{
close_valve
}
}
Step 4: else if (mode == manual)
{
if (tO== tS)
{
while True: # run in a loop
}
if (tC== tO)
{
open_valve()
}
else if (tC > tS)
{
close_valve()
} else {
Continue
}else {
return 'mode must be either manual or auto !!'
}
}
End;
4.1 Hardware Implementation
The hardware implementation consists of the following engineering practical steps
which include the circuit Boarding Process, PCB Design, Soldering of Components,
and Packaging.
Circuit boarding process: The control unit and the sensing unit were simulated on
a bread board to ascertain the workability of all components before the system is
completed. During the course of bread boarding, copper jumper cables were us to
establish connections between components and the Arduino microcontroller. The soil
moisture sensor connected to the wireless transmission link was also simulated. 5V
power supply from the USB was used in the simulation process.
PCB Design: Printed Circuit Board (PCB) is cards made for connecting modern
electronics components together. It represents the electrical schematics in the physical
implementation. However when partitioning the PCB layout, the component
positioning is very important. Components are grouped into logical functional blocks.
The PCB layout of this system was properly designed using Proteus software.
Soldering of components: After the boarding process is completed and the PCB
design is ready, the components were placed on the PCB pad and soldered on the traces
to establish a permanent connection as shown in Figure 4.
Packaging: The Control Unit part of the system was packaged using plastic casing
with the solar panel mounted on it. In packaging the system some design consideration
was taking into account to ensure smooth operation of the system. The solar panel was
properly positioned on the top layer of the casing. The inlet and outlet piping system
were properly sealed and aligned to avoid water leakage. The sensory unit was
packaged in a plastic casing fitted with a cylindrical pipe to enable the soil moisture
sensor to penetrate the soil as depicted in Figure 5. The Figure 6 and 7 shows the
snapshot of control unit and the sensory unit.
Fig 4. The soldered components of the
control unit
Fig 5. The packaging of the Control Unit
Fig 6. The Control Unit Fig 7. The Sensory Unit
4.1 SMIS Mobile Application Implementation
The Android mobile application was developed using React Native. React Native is a
JavaScript framework for building native mobile applications. It allows for large
amounts of inbuilt components like camera, GPS, and APIs. React Native has the native
ability just like normal Android Java, Native Mobile and is faster.
Other JavaScript packages are used to implement this project together with React
Native. These are a subset of libraries that enables some special features. For the
implementation of the Bluetooth communication, react native Ble-Plx was deployed.
Geo Location API is deployed to get to the location of the system. Open Weather API
was also deployed to get the real-time weather of the location. Figure 8 shows the
screenshot of the SMIS mobile application.
Fig 8. Screenshot of SMIS Mobile Application
4.2 Testing
In this section, different tests were conducted to monitor and verify the operations and
performance of the developed system. The key tests conducted in this project are:
1. Unit Testing
2. Integration Testing
3. System Testing
Unit Testing: The system developed consists of different components and two (2)
major subsystem which was coupled together to obtain the whole system. Tests on units
independent of one another were carried out such as the resistance and capacitance
values before circuit connections. The solar panel was tested in order to ensure that it
provides the necessary voltage and current supply when it is connected to charge the
battery. The transistors, capacitors, and resistors were also tested in order to ensure that
they were functioning properly. The NRF and Bluetooth module were individually
tested to ensure functionality and connection from varying range.
The power supply unit of each subsystem consists of 5V solar panel connected to charge
the storage battery of 3.7 V. The test was carried out using millimeters to take the
readings of the solar panel and the battery to ascertain how much voltage is stored and
how long it takes to be fully charged.
The control unit consists of the microcontroller, solenoid valve, the Bluetooth module
and the NRF receiver for communication with the sensor unit. The sensory unit consists
of the soil moisture sensor and the NRF transmitter. Each unit was tested to ensure
compatibility and functionality within the subsystem.
Integration Testing: The interaction between separate subsystems of the project was
evaluated using the integration testing including the user application software. Table 5
shows the various voltage levels obtained at different outputs of the system. The
expected values obtained during the system design and the practical values obtained
during the implementation of the project are also compared.
Table 5. Test Results of the System Power Efficiency.
S/N
Outputs/Inputs
Expected values
Practical values
1
Battery Output at full charge
7.4V
7.8V
2
Input at the Solenoid Valve
3.3V
3.8V
3
Input at microcontroller
5V
5V
4
Input at NRF module
3.3V
3.5V
5
Input at Bluetooth module
3.3V
3.6V
System Testing: The full operation of the system was tested from the user's experience
using the mobile application developed for control of the systems full operation. The
complete system was tested for correct operation by applying the system to irrigate
different soil samples. Figure 9, shows the amount of time the system took to irrigate
different soil samples in different initial states.
Fig. 9. Graph of irrigation time against soil samples.
The result from Fig. 9 shows the time taken for the different soil sample in a one-
square meter container to get irrigated in the three (3) initial states. It can be deduced
from the graph that the system was able to irrigate a effectively a dry soil, sample for
the soil type: sandy soil, loamy and clay soil at 12secs, 20secs and 30 Sec respectively.
While irrigating a partial wet soil for sandy, loamy and clay gave a 10secs, 13secs, and
20 secs respectively. The time taken to irrigate a wet soil sample for sandy, loamy and
clay are 6secs, 7secs, and 12secs respectively.
5 Conclusion
The climatic changes in sub-Sahara Africa nations has made sustainable agriculture
quite challenging due to the harsh sun radiation, scarcity of water which is completely
up to individual’s water generation. These factors however, have been coined towards
the development of a smart solar irrigation system with the aim of addressing the
challenges of power consumption and water management for sustainable agriculture in
the sub-Sahara Africa. The system incorporates solar panels as its power source which
enables the system to work effectively without the need of an AC source. Water
management is achieved by the timely operations of the solenoid valve controlled by
the microcontroller. The experimental result shows effectiveness of the proposed
system with the practical values being so close to the expected result. In conclusion,
the efficiency of the system guarantees that only the right amount of water need is
0
5
10
15
20
25
30
35
Dry Partially Wet Wet
Graph of Irrigation Time against
Soil Samples
Sandy Loamy Clay
supplied to the farmland and it can operate both automatically and manually for
scheduled irrigation. Further study is to enhance the system over the internet using
advanced mobile application.
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... Figure 24 presents the most utilized processors for smart irrigation systems. The most utilized controllers are the ATmega328 [93,103,170,181,182] (Atmel, San José, California, USA) and the ATmega2560 [56,72,81] with five and three papers respectively. The Atmega1281 [133,157] and the LPC2148 (NXP Semiconductors, Eindhoven, The Netherlands) [48,123] [42]. ...
... Ethernet [52,62,72,99,117,131,138,139,146,152,164] GSM [35,36,44,48,51,57,61,64,72,73,79,85,[90][91][92]103,112,129,153,157,[185][186][187][188][189] Wi-Fi [28,34,41,43,46,47,[50][51][52][53]56,59,60,[64][65][66][69][70][71]77,82,84,88,94,95,111,112,116,117,119,120,123,[125][126][127][128][129]132,134,135,139,143,[151][152][153][154][156][157][158]160,163,165,166,168,169,173,182,187,[190][191][192][193][194] ZigBee [5,32,39,42,63,[65][66][67]93,[119][120][121][122][123]128,133,137,144,151,157,175,185,191] Bluetooth [46,53,81,118,129,132,134,156,174,181,195,196] LoRa [14,31,78,95,142,144,145,149,157,196,197] GPRS [44,45,67,73,79,98,101,122,137,157,161,171,179,186,190] MQTT [47,75,86,113,114,160 [73,102] According to the descriptions provided by the different authors of their own implementations, we have verified that the most used communication technology in the different proposals is WiFi, as it can be seen in Figure 25. The reason could be due to is accessibility. ...
... It is followed by the SIM900 GSM module (SIMCOM Wireless Solutions, Shanghai, China ) with nine papers and the NRF24L01 2.4 GHz module (Longruner, Shenzhen, China), the XBee S2 ZigBee module (Digi International Worldwide Headquarters, Hopkins, MN, USA) and the SX1276 LoRa module (Semtech, Camarillo, CA, USA) with three papers each. Some other less utilized modules and chips for wireless communication include GSM modules such as the SIM800 (SIMCOM Wireless Solutions, Shanghai, China) [171,187], the SIM300 (SIMCOM Wireless Solutions, Shanghai, China) [189], Ethernet modules such as the W5100 (SparkFun Electronics, Boulder, CO, USA) [72] or the Ethernet Shield (ELEGOO, Shenzhen, China ) utilized in [139], WiFi modules such as the ESP32 (Espressif Systems, Shanghai, China ) [119], the ESP1 [112], the ATWIN C1500 (Microchip Technology Inc., Chandler, AZ, USA) [191] and the Broadcom (Broadcom, San José, CA, USA) [152], LoRa modules such as the Feather 32u4 (Adafruit Industries, New York, NY, USA) [191] and the LoRa ESP32 [196], 2.4 GHz RF modules such as the C2500 (Mascot, Tainan City, Taiwan) [179] and sub-1 GHz RF modules such as the CC1310 (Texas Instruments, Dallas, TX, USA) [147] and the CC1101 [150], Bluetooth modules such as the HC-05 (Guangzhou HC Information Technology Co., Guangzhou, China) [129,198] and near radio frequency nodules such as the NRF4L (Shen zhen City Huo Chuang Technology Company Ltd., Shenzhen, China) [181]. There other modules that are compatible with several technologies such as the JN5139 that admits both WiFi and ZigBee [121] or the Dragino LoRa GPS shield (DRAGINO TECHNOLOGY CO., LIMITED, Shenzhen, China) [144]. ...
Article
Full-text available
Water management is paramount in countries with water scarcity. This also affects agriculture, as a large amount of water is dedicated to that use. The possible consequences of global warming lead to the consideration of creating water adaptation measures to ensure the availability of water for food production and consumption. Thus, studies aimed at saving water usage in the irrigation process have increased over the years. Typical commercial sensors for agriculture irrigation systems are very expensive, making it impossible for smaller farmers to implement this type of system. However, manufacturers are currently offering low-cost sensors that can be connected to nodes to implement affordable systems for irrigation management and agriculture monitoring. Due to the recent advances in IoT and WSN technologies that can be applied in the development of these systems, we present a survey aimed at summarizing the current state of the art regarding smart irrigation systems. We determine the parameters that are monitored in irrigation systems regarding water quantity and quality, soil characteristics and weather conditions. We provide an overview of the most utilized nodes and wireless technologies. Lastly, we will discuss the challenges and the best practices for the implementation of sensor-based irrigation systems.
... Figure 2.24 presents the most utilized processors for smart irrigation systems. The most utilized controllers are the ATmega328 [143,154,221,231,232] and the ATmega2560 [10,122,131] with five and three papers respectively. The Atmega1281 [184,208] and the LPC2148 [98,174] are both utilized in two papers each. ...
... Ethernet [102,112,122,150,168,182,189,190,197,203,215] GSM [84, 85, 93, 98, 101, 107, 111, 114, 122, 123, 129, 135, 140-142, 154, 163, 180, 204, 208, 235-239] Wi-Fi [78, 83, 90, 92, 95, 97, 100-103, 106, 109, 110, 114-116, 119-121, 127, 132, 134, 138, 144, 145, 162, 163, 167, 168, 170, 171, 174, 176, 177, 178-180, 183, 185, 186, 190, 194, 202-205, 207-209, 211, 214, 216, 217, 219, 220, 224, 232, 237, 240-244] ZigBee [81, 88, 91, 113, 115-117, 143, 148, 170, 171-174, 189, 184, 188, 195, 202, 208, 226, 235, 241] Bluetooth [95,103,131,169,180,183,185,207,225,231,245,246] LoRa [5,106,128,145,193,195,196,200,208,246,247] GPRS [64,93,94,117,123,129,149,152,173,188,208,212,222,236,240] MQTT [97,125,136,164,165,211,226,227] 4G [94,106,128,189,192,196,203] 6LoWPAN [125,198] We also observe that, in a large number of works, the end-users access the data, obtained during the monitoring process or to carry out the control of the system, through APPs or WEBs. Most of these communications are done through mobile devices using wireless technologies. ...
... It is followed by the SIM900 GSM module with nine papers and the NRF24L01 2.4 GHz module, the XBee S2 ZigBee module, and the SX1276 LoRa module with three papers each. Some other less utilized modules and chips for wireless communication include GSM modules such as the SIM800 [222,237], the SIM300 [239], Ethernet modules such as the W5100 [132] or the Ethernet Shield utilized in [190], WiFi modules such as the ESP32 [170], the ESP1 [163], the ATWIN C1500 [241] and the Broadcom [203], LoRa modules such as the Feather 32u4 [241] and the LoRa ESP32 [246], 2.4 GHz RF modules such as the C2500 [64] and sub-1 GHz RF modules such as the CC1310 [198] and the CC1101 [201], Bluetooth modules such as the HC-05 [180,248] and near radio frequency nodules such as the NRF4L [231]. There are other modules that are compatible with several technologies such as the JN5139 that admits both WiFi and ZigBee [172] or the Dragino LoRa GPS (Global Positioning System) shield [195]. ...
Thesis
The introduction of technological solutions in agriculture allows reducing the use of resources and increasing the production of the crops. Furthermore, the quality of the water for irrigation can be monitored to ensure the safety of the produce for human consumption. However, the remote location of most fields presents a problem for providing wireless coverage to the sensing nodes and actuators deployed on the fields and the irrigation water canals. The work presented in this thesis addresses the problem of enabling wireless communication among the electronic devices deployed for water quality and field monitoring through a heterogeneous communication protocol and architecture. The first part of the dissertation introduces Precision Agriculture (PA) systems and the importance of water quality and field monitoring. In addition, the technologies that enable wireless communication in PA systems and the use of alternative solutions such as Internet of Underground Things (IoUT) and Unmanned Aerial Vehicles (UAV) are introduced as well. Then, an in-depth analysis on the state of the art regarding the sensors for water, field and meteorology monitoring and the most utilized wireless technologies in PA is performed. Furthermore, the current trends and challenges for Internet of Things (IoT) irrigation systems, including the alternate solutions previously introduced, have been discussed in detail. Then, the architecture for the proposed system is presented, which includes the areas of interest for the monitoring activities comprised of the canal and field areas. Moreover, the description and operation algorithms of the sensor nodes contemplated for each area is provided. The next chapter details the proposed heterogeneous communication protocol including the messages and alerts of the system. Additionally, a new tree topology for hybrid LoRa/WiFi multi-hop networks is presented. The specific additional functionalities intended for the proposed architecture are described in the following chapter. It includes data aggregation algorithms for the proposed topology, an overview on the security threats of PA systems, energy-saving and fault-tolerance algorithms, underground communication for IoUT, and the use of drones for data acquisition. Then, the simulation results for the solutions previously proposed are presented. Finally, the tests performed in real environments for the presented heterogeneous protocol, the different deployment strategies for the utilized nodes, the energy consumption, and a functionality for fruit quantification are discussed. These tests demonstrate the validity of the proposed heterogeneous architecture and communication protocol.
... Abayomi-Alli et al. [15] Create an automatic irrigation system that uses solar energy. This will offer a financially sensible replacement for the conventional irrigation technique. ...
Article
The desire of man to be in control of everything around him in recent times is born out of the rapid development of smart technologies as everything now depends on the internet. Irrigation system is also becoming smart by using modern technologies, which is more advantageous than traditional irrigation methods. In this work, a smart irrigation system is developed that automates the irrigation process powered by solar energy. This proposed system can optimize the use of water based on different data, such as soil moisture level, weather prediction, and soil temperature. A soil moisture sensor that utilizes IoT technology will be inserted into the farmland to detect the moisture level and then notify the farmer about the current condition of the soil through a developed mobile application. Furthermore, the system can automatically turn ON the motor pump from the mobile app to irrigate the farm when the moisture level and soil temperature are below 50% and will automatically turn OFF the pump after fulfilling the demand of the soil when the moisture level and temperature is above 75%. The whole proposed system is controlled by a microcontroller and a DC power is generated from the solar panel which helps to keep the system working at any time of the day. All these features will make the irrigation system much smarter, more economical, and more eco-friendly. In conclusion, this system is recommended for use by farmers who lives in areas with low access to constant water supply.
... Penelitian berfokus pada monitoring kinerja generator tenaga surya dan tidak menggunakan nRF24L01. Implementasi nRF24L01 dan tenaga surya untuk sistem irigasi cerdas sudah dilakukan (Abayomi-Alli et al., 2018). Penelitian ini berfokus pada implementasi sistem dan tidak berfokus pada kualitas komunikasi data. ...
Article
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... Also, the system was designed with features that enables plant diseases to be detected and adequately controlled. Works are ongoing to improve farming by applying computation techniques [27], encouraging organic farming [28] and also attaining sustainability [29][30]. ...
Chapter
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Recent development in agricultural techniques has led to an increase in yield and has proven to be more environmentally friendly in their applications. With the continuous increase in the world population, food demand is expected to increase simultaneously and a way to meet such immense demand is to intensify contemporary agricultural measures for ensuring food availability and security, which is also one of the aims of sustainable development goals (SDG)-2—zero hunger of United Nations. This paper discusses the design of hydroponics; a modern, clean and environmentally friendly technique for growing vegetables in an appropriately regulated environment without soil and natural sunlight but with the aid of temperature sensors, actuators, artificial lighting systems, nutrient solutions, and heating/cooling systems for maintaining water and air temperatures using National Instrument (NI) LabVIEW software package. Hydroponics as a contemporary agricultural technique for growing leafy vegetables has proven successful in its implementation and guarantees all-year production regardless of environmental or climatic conditions. The automation of the entire growth process in the system makes it possible for the procedures to be carried out effectively with little or no human interference. The problem of scarcity and unavailability of rare vegetable varieties with high demand can be reduced to its barest minimum with the implementation of the automated system.
... It involves processing of real-time images to provide vision to the computer. Each frame in the image will be processed to find the object in the image [22,23]. ...
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