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International Journal of Reconfigurable and Embedded Systems (IJRES)
Vol. 13, No. 1, March 2024, pp. 105~110
ISSN: 2089-4864, DOI: 10.11591/ijres.v13.i1.pp105-110  105
Journal homepage: http://ijres.iaescore.com
Design of Arduino UNO based smart irrigation system for real
time applications
Palanisamy Ramasamy1
, Nagarajan Pandian2
, Krishnamurthy Mayathevar3
, Ramkumar Ravindran4
,
Srinivasa Rao Kandula5
, Selvabharathi Devadoss1
, Selvakumar Kuppusamy1
1
Department of Electrical and Electronics Engineering, SRM Institute of Science and Technology, Kattankulathur, India
2
Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, Vadapalani, India
3
Department of Electronics and Communication Engineering, PSNA College of Engineering and Technology, Dindigul, India
4
Department of Electrical and Electronics Engineering, Dhanalakshmi Srinivasan University, Tiruchirappalli, India
5
Department of Electronics and Communication Engineering, Dhanekula Institute of Engineering and Technology, Vijyawada, India
Article Info ABSTRACT
Article history:
Received Mar 9, 2023
Revised Apr 28, 2023
Accepted May 9, 2023
The fundamental principle of the paper is that the soil moisture sensor obtains
the moisture content level of the soil sample. The water pump is automatically
activated if the moisture content is insufficient, which causes water to flow
into the soil. The water pump is immediately turned off when the moisture
content is high enough. Smart home, smart city, smart transportation, and
smart farming are just a few of the new intelligent ideas that internet of things
(IoT) includes. The goal of this method is to increase productivity and
decrease manual labour among farmers. In this paper, we present a system for
monitoring and regulating water flow that employs a soil moisture sensor to
keep track of soil moisture content as well as the land’s water level to keep
track of and regulate the amount of water supplied to the plant. The device
also includes an automated led lighting system.
Keywords:
Arduino UNO
Internet of things
Real time system
Sensors
Smart irrigation This is an open access article under the CC BY-SA license.
Corresponding Author:
Palanisamy Ramasamy
Department of Electrical and Electronics Engineering, SRM Institute of Science and Technology
Kattankulathur, Tamil Nadu, India
Email: krspalani@gmail.com
1. INTRODUCTION
Numerous variables, including soil quality, water volume, pH level, and sunlight, are crucial to
agriculture. For the plant to develop properly in the soil, each of these quantities needs to be supplied in a
certain amount. Consequently, this initiative automates and controls the water flow and content [1]–[4]. The
project utilizes various sensors to collect environmental data such as temperature, humidity, and soil moisture
content, which are then processed by the Arduino UNO board to determine the optimal amount of water needed
for the plants. The system then automatically controls the water supply to the plants based on the readings from
the sensors, ensuring that the plants receive just the right amount of water.
In India, where agriculture is one of the top industries in the nation and is reliant on rainfall, irrigation
is very important. This has an issue with uneven and erratic water distribution in the soils [5]. The fertility and
moisture of the earth are key factors in the development of soil-based plants. To address these issues, we
combine an Arduino UNO controller with a soil moisture monitor, a DC water pump, light dependent resisters
(LDRs), and light emiting diodes (LEDs) [6]–[8]. The two leads that make up the soil moisture sensor are used
to gauge the amount of water present in the earth. These leads enable the flow of current through the soil, which
calculates the resistance value to determine the soil’s wetness content [9]. More water in the soil will increase
its ability to transmit electricity, resulting in lower resistance values and higher moisture levels. Similar to how
 ISSN: 2089-4864
Int J Reconfigurable & Embedded Syst, Vol. 13, No. 1, March 2024: 105-110
106
soil will transmit less electricity if there is less water present, low moisture levels are accompanied by high
resistance values [10]–[12].
A photo resistor is a type of light-controlled variable resistor, also known as an LDR. A photo resistor
shows photoconductivity when the resistance decreases as the intensity of the incident light increases.
In light-sensitive detection circuits as well as light- and dark-activated switching circuits, a photo resistor can
be used [13]. High resistance semiconductors are used to create light resistors. A photo resistor can have a
resistance as high as several mega ohms (M) in complete darkness, but only a few hundred ohms in complete
illumination [14]–[16]. A pump is a mechanical device used to transport fluids (liquids, gases, or occasionally
slurries). Depending on how they transport the fluid, pumps can be divided into three main categories [17].
The project’s foundation is a microcontroller device called Arduino UNO. The C-based Arduino programming
language is used to operate it. Students can use it more easily because the programme is open-source. The
microprocessor used in the Arduino UNO is an ATmega328P [18]. It has numerous analogue and digital pins
that are used for programming and controlling various types of electronic devices. It has 6 programmable
analogue pins and 14 digital pins. It is linked to a computer via the Arduino IDE [19], [20]. The goal is to
automate agriculture, increase field productivity overall, ensure proper plant maintenance and growth, save
manpower and water, improve soil health through real-time sensing and control, assess soil quality, and make
sure the right type of soil is being used for a particular type of plant. It is suggested that an automated irrigation
system be used, where the right sensors are used to sense the soil conditions and a microcontroller can control
the amount of water delivered to the soil based on those conditions. The farmer will keep an eye on the soil’s
nutrient level. The plant’s root zone contains sensors that measure the moisture in the soil.
2. SENSORS
The volumetric water content of soil is determined using the soil moisture sensor. By measuring the
soil’s permittivity, which is a function of the amount of water present, this sensor employs capacitance to
determine the water content that is present in the soil [21], [22]. The volumetric amount of water in the soil is
calculated by placing this sensor into the sample soil, and the results are expressed as a percentage. Soil
moisture sensors use an indirect method to measure the volumetric water content by substituting another soil
property, like resistance or dielectric constant, for the labor-intensive task of directly measuring the water
content in free soil [23]–[25]. It is necessary to calibrate the relationship between the recorded component and
soil moisture because it can vary depending on the type of soil, soil temperature, or electric conductivity. In
general, sensors that measure soil wetness by volume are referred to as soil moisture sensors. Another class of
sensors, commonly known as soil water potential sensors, measure the water potential, a different aspect of
soil moisture [26]. These sensors have tension and gypsum blocks.
LDR are light sensitive resistors, and as the amount of light they are exposed to increases, their
resistance decreases. LDRs are light-sensitive electronics that are most frequently used to measure or indicate
the presence or absence of light. When the LDR sensor is exposed to light, the resistance decreases drastically,
sometimes even to a few ohms, depending on the light intensity. In the dark, their resistance is very high,
sometimes reaching up to 1 M. LDRs are nonlinear sensors with variable sensitivity depending on the
wavelength of applied light. They have a wide range of uses, but occasionally technology like photodiodes and
phototransistors renders them obsolete. LDRs made of lead or cadmium have been outlawed in some nations
due to environmental safety concerns.
3. CONTROL STRATEGY
The block layout of the suggested system is shown in Figure 1. The graph Figure 2 between the digital
readings provided by the soil moisture sensor in Figure 2(a) and amount of moisture in the soil in Figure 2(b).
The water pump is activated when the soil moisture digital number is below a certain threshold. The number
is zero and the water pump is turned off when there is too much water in the soil. The system can help farmers
save water and energy costs, increase crop yield, and improve the overall health of the plants. Additionally, the
project can be modified and expanded to incorporate other features such as fertilization, pest control, and
remote monitoring.
The measurements of light intensity have been plotted. The strength varies between around 1,000 cd
during the day and 500 cd at night. In Figure 3 shows the moisture content of soil has been plotted against time.
The moisture content was measured at an interval of 15 minutes. The ability of the soil to hold water has been
mapped against time in Figure 4. Five hours apart, the absorbing ability was assessed. The system is designed
to optimize water usage by providing just the right amount of water to the plants, thus reducing water and
energy costs, improving crop yield, and promoting plant health. The project is cost-effective, easy to build and
use, and can be implemented in small or large-scale irrigation systems. The project has the potential to
Int J Reconfigurable & Embedded Syst ISSN: 2089-4864 
Design of Arduino UNO based smart irrigation system for real time applications (Palanisamy Ramasamy)
107
revolutionize irrigation in agriculture and can be modified and expanded to incorporate additional features such
as fertilization, pest control, and remote monitoring.
Figure 1. Block diagram of proposed system
(a) (b)
Figure 2. Proposed system (a) digital values given by the soil moisture sensor and (b) moisture in the soil
Figure 3. Comparison of moisture content with time Figure 4. Water absorbing capacity with time
4. EXPERIMENTAL RESULTS AND DISCUSSION
Figure 5 depicts the system’s experimental setup and the source code that is operating on the Arduino
IDE platform. The ATMEGA328 microcontroller on the Arduino UNO development board is linked to the soil
moisture sensor, the LDR, and the LEDs. According to test results, the soil moisture sensor constantly monitors
the soil’s moisture content. If the moisture level is low, the water pump is automatically turned on, and if the
moisture level is adequate, it is turned off. The LDR senses the light intensity throughout the day and when the
intensity drops below 600 cd (around nighttime) the LEDs glow. Circuit connection of proposed system is
shown in Figure 6.
A moisture sensing probe is inserted in the soil next to the sprinkler head in the irrigation system
described above in order to generate an electrical signal indicating the amount of moisture present in the soil
surrounding the probe. The irrigation system described above uses an immiscible DC pump that delivers water
under pressure through a valve. Figure 7 shows experimental results, which the representation of moisture level
and moisture content in the soil vs time is shown in Figures 7(a) and 7(b).
 ISSN: 2089-4864
Int J Reconfigurable & Embedded Syst, Vol. 13, No. 1, March 2024: 105-110
108
Figure 5. Experiment setup Figure 6. Circuit connection of proposed system
(a) (b)
Figure 7. Experimental results (a) moisture level representation and (b) moisture content in the soil vs time
A motor driver circuit links the 12 V DC pump to the soil moisture monitor. The path of the current
flowing from the DC motor determines which of its two working directions clockwise or counter clockwise it
will operate in. The microprocessor will supply the inputs A and B. The soil moisture sensor detects the amount
of moisture in the soil; if the moisture is low, it sends a value of 1 or higher to the DC pump, which then
supplies water; if the moisture is adequate, the sensor sends a digital value of 0, which turns off the pump. In
the circuit, there is an LED illumination setup. The LDR detects light intensity all day long; when the intensity
reaches 500, signifying nighttime, the LEDs begin to glow.
5. CONCLUSION
This project uses an Arduino UNO, a soil moisture sensor, and an LDR to decrease manual labour,
improve efficiency, and conserve water. The method works well because it automates and regulates plant
watering without the need for manual labour. In accordance with the sort of soil, it gives the plant water.
According to the digital values obtained from the soil moisture sensor, the motor driver circuit in this system,
which operates the DC immiscible pump, can be remotely controlled to control the flow of water. Additionally,
cost-effective, this technology can support agriculture in dry regions. This design’s limitation is the
requirement for manual testing in the event that any specific component or gadget fails.
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BIOGRAPHIES OF AUTHORS
Palanisamy Ramasamy received the bachelor of engineering degree in electrical
and electronics engineering from Anna University, India, in 2011, and the masters of technology
degree in power electronics and drives and the Ph.D. degree in power electronics from the SRM
Institute of Science and Technology, Chennai, India, in 2013 and 2019, respectively. He is
currently working as an assistant professor with the Department of Electrical Engineering, SRM
Institute of Science and Technology. He has published more than 95 international and national
journals. His research interests include power electronics multilevel inverters, various PWM
techniques for power converters, FACTS controllers, and grid connected photovoltaic systems.
He can be contacted at email: krspalani@gmail.com.
Nagarajan Pandian received a bachelor of engineering degree in electronics and
communication engineering from Anna University, Chennai, in 2007, a master of engineering
degree in applied electronics from Anna University, Trichy in 2009, and a Ph.D. degree from
Anna University, Chennai in 2015. He is currently working as an associate professor in the
Department of Electronics and Communication Engineering at SRM Institute of Science and
Technology, Vadapalani, Chennai, India. His research interests include FPGA implementation,
low-power VLSI systems, device modeling, and VLSI architectures for image processing. He
can be contacted at email: nagarajan.pandiyan@gmail.com.
 ISSN: 2089-4864
Int J Reconfigurable & Embedded Syst, Vol. 13, No. 1, March 2024: 105-110
110
Krishnamurthy Mayathevar received the master of engineering and bachelor of
engineering degrees from Anna University in 2008 and 2006, respectively, and has awarded
doctorate during the year 2021 from Anna University. He is currently working as an assistant
professor of Electronics and Communication Engineering Department, PSNA College of
Engineering and Technology, Dindigul, India. He can be contacted at email:
krishnamurthy184@gmail.com.
Ramkumar Ravindran is currently working as an assistant professor in the
Department of Electrical and Electronics Engineering at Dhanalakshmi Srinivasan University,
Trichy. He obtained his Ph.D. under Faculty of Electrical Engineering from Anna University
(2022), Chennai. He completed his master of engineering in Sethu Institute of Technology
(2012), Madurai. He completed his bachelor of engineering in K.L.N. College of Information
Technology (2008), Madurai. He has published more than 35 Scopus indexed journals and 6
SCI journals in his field. He has 11 years of teaching experience and 1-year industrial
experience. His area of interest is power electronic converters, renewable energy and micro
grid. He can be contacted at email: 2019ramkr@gmail.com.
Srinivasa Rao Kandula is currently working as a professor in the Department of
Electronics and Communication Engineering at Dhanekula Institute of Engineering and
Technology, Ganguru, Vijayawada, Andhra Pradesh. He obtained his Ph.D. under the
Department of Electronics and Communication Engineering from Jawaharlal Nehru
Technological University Kakinada (2016), Kakinada. He completed his masters of technology
in E.C.E from Jawaharlal Nehru Technological University Kakinada (2007), Kakinada. He
completed his bachelor technology in E.C.E from Daita Mahdusudana Sastry Sri Venkateswara
Hindu College of engineering (2002), Machilipatnam. He has 19 years of teaching experience
and 1-year of Industrial experience. He has completed a LRDE funding consultancy project and
he has published 15 peer reviewed journals in various International Journals. His area of interest
is wireless communications, digital signal processing and IoT. He can be contacted at email:
ksrinivas.ece@gmail.com.
Selvabharathi Devadoss received bachelor of engineering degree in ECE from
Valliammai Engineering College, affiliated to Anna University, Tamil Nadu, India in the 2007,
and received the masters of technology degree in power electronics and drives from SRM
University, Kattankulathur, Tamil Nadu, India in 2012. He is currently working as an assistant
professor in EEE Department at SRM Institute of Science and Technology, Kattankulathur
India. His research interest includes advancing the battery health management techniques for
real time monitoring and diagnostics. He can be contacted at email: dsbsrm@gmail.com.
Selvakumar Kuppusamy received bachelor of engineering degree in electrical
and electronics engineering, master of engineering degree in power system engineering both
from Anna University and received Ph.D. in deregulated power systems from SRM University,
Kattankulathur, Tamil Nadu, India in 2018. He is currently working as an assistant professor in
SRM University. His research interests include unit commitment, economic dispatch, power
system optimization and smart grid, distributed generation in power system. He can be
contacted at email: selvakse@gmail.com.

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Design of Arduino UNO based smart irrigation system for real time applications

  • 1. International Journal of Reconfigurable and Embedded Systems (IJRES) Vol. 13, No. 1, March 2024, pp. 105~110 ISSN: 2089-4864, DOI: 10.11591/ijres.v13.i1.pp105-110  105 Journal homepage: http://ijres.iaescore.com Design of Arduino UNO based smart irrigation system for real time applications Palanisamy Ramasamy1 , Nagarajan Pandian2 , Krishnamurthy Mayathevar3 , Ramkumar Ravindran4 , Srinivasa Rao Kandula5 , Selvabharathi Devadoss1 , Selvakumar Kuppusamy1 1 Department of Electrical and Electronics Engineering, SRM Institute of Science and Technology, Kattankulathur, India 2 Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, Vadapalani, India 3 Department of Electronics and Communication Engineering, PSNA College of Engineering and Technology, Dindigul, India 4 Department of Electrical and Electronics Engineering, Dhanalakshmi Srinivasan University, Tiruchirappalli, India 5 Department of Electronics and Communication Engineering, Dhanekula Institute of Engineering and Technology, Vijyawada, India Article Info ABSTRACT Article history: Received Mar 9, 2023 Revised Apr 28, 2023 Accepted May 9, 2023 The fundamental principle of the paper is that the soil moisture sensor obtains the moisture content level of the soil sample. The water pump is automatically activated if the moisture content is insufficient, which causes water to flow into the soil. The water pump is immediately turned off when the moisture content is high enough. Smart home, smart city, smart transportation, and smart farming are just a few of the new intelligent ideas that internet of things (IoT) includes. The goal of this method is to increase productivity and decrease manual labour among farmers. In this paper, we present a system for monitoring and regulating water flow that employs a soil moisture sensor to keep track of soil moisture content as well as the land’s water level to keep track of and regulate the amount of water supplied to the plant. The device also includes an automated led lighting system. Keywords: Arduino UNO Internet of things Real time system Sensors Smart irrigation This is an open access article under the CC BY-SA license. Corresponding Author: Palanisamy Ramasamy Department of Electrical and Electronics Engineering, SRM Institute of Science and Technology Kattankulathur, Tamil Nadu, India Email: krspalani@gmail.com 1. INTRODUCTION Numerous variables, including soil quality, water volume, pH level, and sunlight, are crucial to agriculture. For the plant to develop properly in the soil, each of these quantities needs to be supplied in a certain amount. Consequently, this initiative automates and controls the water flow and content [1]–[4]. The project utilizes various sensors to collect environmental data such as temperature, humidity, and soil moisture content, which are then processed by the Arduino UNO board to determine the optimal amount of water needed for the plants. The system then automatically controls the water supply to the plants based on the readings from the sensors, ensuring that the plants receive just the right amount of water. In India, where agriculture is one of the top industries in the nation and is reliant on rainfall, irrigation is very important. This has an issue with uneven and erratic water distribution in the soils [5]. The fertility and moisture of the earth are key factors in the development of soil-based plants. To address these issues, we combine an Arduino UNO controller with a soil moisture monitor, a DC water pump, light dependent resisters (LDRs), and light emiting diodes (LEDs) [6]–[8]. The two leads that make up the soil moisture sensor are used to gauge the amount of water present in the earth. These leads enable the flow of current through the soil, which calculates the resistance value to determine the soil’s wetness content [9]. More water in the soil will increase its ability to transmit electricity, resulting in lower resistance values and higher moisture levels. Similar to how
  • 2.  ISSN: 2089-4864 Int J Reconfigurable & Embedded Syst, Vol. 13, No. 1, March 2024: 105-110 106 soil will transmit less electricity if there is less water present, low moisture levels are accompanied by high resistance values [10]–[12]. A photo resistor is a type of light-controlled variable resistor, also known as an LDR. A photo resistor shows photoconductivity when the resistance decreases as the intensity of the incident light increases. In light-sensitive detection circuits as well as light- and dark-activated switching circuits, a photo resistor can be used [13]. High resistance semiconductors are used to create light resistors. A photo resistor can have a resistance as high as several mega ohms (M) in complete darkness, but only a few hundred ohms in complete illumination [14]–[16]. A pump is a mechanical device used to transport fluids (liquids, gases, or occasionally slurries). Depending on how they transport the fluid, pumps can be divided into three main categories [17]. The project’s foundation is a microcontroller device called Arduino UNO. The C-based Arduino programming language is used to operate it. Students can use it more easily because the programme is open-source. The microprocessor used in the Arduino UNO is an ATmega328P [18]. It has numerous analogue and digital pins that are used for programming and controlling various types of electronic devices. It has 6 programmable analogue pins and 14 digital pins. It is linked to a computer via the Arduino IDE [19], [20]. The goal is to automate agriculture, increase field productivity overall, ensure proper plant maintenance and growth, save manpower and water, improve soil health through real-time sensing and control, assess soil quality, and make sure the right type of soil is being used for a particular type of plant. It is suggested that an automated irrigation system be used, where the right sensors are used to sense the soil conditions and a microcontroller can control the amount of water delivered to the soil based on those conditions. The farmer will keep an eye on the soil’s nutrient level. The plant’s root zone contains sensors that measure the moisture in the soil. 2. SENSORS The volumetric water content of soil is determined using the soil moisture sensor. By measuring the soil’s permittivity, which is a function of the amount of water present, this sensor employs capacitance to determine the water content that is present in the soil [21], [22]. The volumetric amount of water in the soil is calculated by placing this sensor into the sample soil, and the results are expressed as a percentage. Soil moisture sensors use an indirect method to measure the volumetric water content by substituting another soil property, like resistance or dielectric constant, for the labor-intensive task of directly measuring the water content in free soil [23]–[25]. It is necessary to calibrate the relationship between the recorded component and soil moisture because it can vary depending on the type of soil, soil temperature, or electric conductivity. In general, sensors that measure soil wetness by volume are referred to as soil moisture sensors. Another class of sensors, commonly known as soil water potential sensors, measure the water potential, a different aspect of soil moisture [26]. These sensors have tension and gypsum blocks. LDR are light sensitive resistors, and as the amount of light they are exposed to increases, their resistance decreases. LDRs are light-sensitive electronics that are most frequently used to measure or indicate the presence or absence of light. When the LDR sensor is exposed to light, the resistance decreases drastically, sometimes even to a few ohms, depending on the light intensity. In the dark, their resistance is very high, sometimes reaching up to 1 M. LDRs are nonlinear sensors with variable sensitivity depending on the wavelength of applied light. They have a wide range of uses, but occasionally technology like photodiodes and phototransistors renders them obsolete. LDRs made of lead or cadmium have been outlawed in some nations due to environmental safety concerns. 3. CONTROL STRATEGY The block layout of the suggested system is shown in Figure 1. The graph Figure 2 between the digital readings provided by the soil moisture sensor in Figure 2(a) and amount of moisture in the soil in Figure 2(b). The water pump is activated when the soil moisture digital number is below a certain threshold. The number is zero and the water pump is turned off when there is too much water in the soil. The system can help farmers save water and energy costs, increase crop yield, and improve the overall health of the plants. Additionally, the project can be modified and expanded to incorporate other features such as fertilization, pest control, and remote monitoring. The measurements of light intensity have been plotted. The strength varies between around 1,000 cd during the day and 500 cd at night. In Figure 3 shows the moisture content of soil has been plotted against time. The moisture content was measured at an interval of 15 minutes. The ability of the soil to hold water has been mapped against time in Figure 4. Five hours apart, the absorbing ability was assessed. The system is designed to optimize water usage by providing just the right amount of water to the plants, thus reducing water and energy costs, improving crop yield, and promoting plant health. The project is cost-effective, easy to build and use, and can be implemented in small or large-scale irrigation systems. The project has the potential to
  • 3. Int J Reconfigurable & Embedded Syst ISSN: 2089-4864  Design of Arduino UNO based smart irrigation system for real time applications (Palanisamy Ramasamy) 107 revolutionize irrigation in agriculture and can be modified and expanded to incorporate additional features such as fertilization, pest control, and remote monitoring. Figure 1. Block diagram of proposed system (a) (b) Figure 2. Proposed system (a) digital values given by the soil moisture sensor and (b) moisture in the soil Figure 3. Comparison of moisture content with time Figure 4. Water absorbing capacity with time 4. EXPERIMENTAL RESULTS AND DISCUSSION Figure 5 depicts the system’s experimental setup and the source code that is operating on the Arduino IDE platform. The ATMEGA328 microcontroller on the Arduino UNO development board is linked to the soil moisture sensor, the LDR, and the LEDs. According to test results, the soil moisture sensor constantly monitors the soil’s moisture content. If the moisture level is low, the water pump is automatically turned on, and if the moisture level is adequate, it is turned off. The LDR senses the light intensity throughout the day and when the intensity drops below 600 cd (around nighttime) the LEDs glow. Circuit connection of proposed system is shown in Figure 6. A moisture sensing probe is inserted in the soil next to the sprinkler head in the irrigation system described above in order to generate an electrical signal indicating the amount of moisture present in the soil surrounding the probe. The irrigation system described above uses an immiscible DC pump that delivers water under pressure through a valve. Figure 7 shows experimental results, which the representation of moisture level and moisture content in the soil vs time is shown in Figures 7(a) and 7(b).
  • 4.  ISSN: 2089-4864 Int J Reconfigurable & Embedded Syst, Vol. 13, No. 1, March 2024: 105-110 108 Figure 5. Experiment setup Figure 6. Circuit connection of proposed system (a) (b) Figure 7. Experimental results (a) moisture level representation and (b) moisture content in the soil vs time A motor driver circuit links the 12 V DC pump to the soil moisture monitor. The path of the current flowing from the DC motor determines which of its two working directions clockwise or counter clockwise it will operate in. The microprocessor will supply the inputs A and B. The soil moisture sensor detects the amount of moisture in the soil; if the moisture is low, it sends a value of 1 or higher to the DC pump, which then supplies water; if the moisture is adequate, the sensor sends a digital value of 0, which turns off the pump. In the circuit, there is an LED illumination setup. The LDR detects light intensity all day long; when the intensity reaches 500, signifying nighttime, the LEDs begin to glow. 5. CONCLUSION This project uses an Arduino UNO, a soil moisture sensor, and an LDR to decrease manual labour, improve efficiency, and conserve water. The method works well because it automates and regulates plant watering without the need for manual labour. In accordance with the sort of soil, it gives the plant water. According to the digital values obtained from the soil moisture sensor, the motor driver circuit in this system, which operates the DC immiscible pump, can be remotely controlled to control the flow of water. Additionally, cost-effective, this technology can support agriculture in dry regions. This design’s limitation is the requirement for manual testing in the event that any specific component or gadget fails. REFERENCES [1] Y. Kim and R. G. Evans, “Software design for wireless sensor-based site-specific irrigation,” Computers and Electronics in Agriculture, vol. 66, no. 2, pp. 159–165, May 2009, doi: 10.1016/j.compag.2009.01.007. [2] D. K. Fisher and H. Kebede, “A low-cost microcontroller-based system to monitor crop temperature and water status,” Computers and Electronics in Agriculture, vol. 74, no. 1, pp. 168–173, Oct. 2010, doi: 10.1016/j.compag.2010.07.006. [3] A. Al Balushi, “Execution of cloud scheduling algorithms,” International Innovative Research Journal of Engineering and Technology, vol. 2, no. 4, pp. 62–65, Jun. 2017, doi: 10.32595/iirjet.org/v2i4.2017.39. [4] Y. Kim, J. D. Jabro, and R. G. Evans, “Wireless lysimeters for real-time online soil water monitoring,” Irrigation Science, vol. 29, no. 5, pp. 423–430, Sep. 2011, doi: 10.1007/s00271-010-0249-x. [5] K. Selvakumar, R. Palanisamy, P. Nikhil, D. Karthikeyan, and D. Selvabharathi, “Control system of automatic garage using programmable logic controller,” TELKOMNIKA (Telecommunication Computing Electronics and Control), vol. 18, no. 5, pp. 2654- 2664, Oct. 2020, doi: 10.12928/telkomnika.v18i5.14398. [6] I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “A survey on sensor networks,” IEEE Communications Magazine, vol. 40, no. 8, pp. 102–114, Aug. 2002, doi: 10.1109/MCOM.2002.1024422.
  • 5. Int J Reconfigurable & Embedded Syst ISSN: 2089-4864  Design of Arduino UNO based smart irrigation system for real time applications (Palanisamy Ramasamy) 109 [7] J. Yick, B. Mukherjee, and D. Ghosal, “Wireless sensor network survey,” Computer Networks, vol. 52, no. 12, pp. 2292–2330, Aug. 2008, doi: 10.1016/j.comnet.2008.04.002. [8] M. Winkler, K. Tuchs, K. Hughes, and G. Barclay, “Theoretical and practical aspects of military wireless sensor networks,” Journal of Telecommunications and Information Technology, vol. 2, pp. 37–45, 2008. [9] A. Alemdar and M. Ibnkahla, “A survey of wireless sensor networks,” in Adaptation and Cross Layer Design in Wireless Networks, CRC Press, 2008, pp. 243–262. [10] A. Hinostroza and J. Tarrillo, “Wireless sensor network for environmental monitoring of cultural heritage,” in Proceedings of the 11th International Conference on Sensor Networks, 2022, pp. 171–175, doi: 10.5220/0010916700003118. [11] G. López, V. Custodio, and J. I. Moreno, “LOBIN: e-textile and wireless-sensor-network-based platform for healthcare monitoring in future hospital environments,” IEEE Transactions on Information Technology in Biomedicine, vol. 14, no. 6, pp. 1446–1458, Nov. 2010, doi: 10.1109/TITB.2010.2058812. [12] J. M. Corchado, J. Bajo, D. I. Tapia, and A. Abraham, “Using heterogeneous wireless sensor networks in a telemonitoring system for healthcare,” IEEE Transactions on Information Technology in Biomedicine, vol. 14, no. 2, pp. 234–240, Mar. 2010, doi: 10.1109/TITB.2009.2034369. [13] R. Palanisamy, P. S. Kumar, M. P. Kiran, A. Mahto, M. Irfan, and M. Bhowmick, “Arduino based accident prevention and auto intimation system,” Indonesian Journal of Electrical Engineering and Computer Science (IJEECS), vol. 17, no. 3, pp. 1275-1280, Mar. 2020, doi: 10.11591/ijeecs.v17.i3.pp1275-1280. [14] M. E. Gavito, P. S. Curtis, T. N. Mikkelsen, and I. Jakobsen, “Interactive effects of soil temperature, atmospheric carbon dioxide and soil N on root development, biomass and nutrient uptake of winter wheat during vegetative growth,” Journal of Experimental Botany, vol. 52, no. 362, pp. 1913–1923, Sep. 2001, doi: 10.1093/jexbot/52.362.1913. [15] M. P. González-Dugo, M. S. Moran, L. Mateos, and R. Bryant, “Canopy temperature variability as an indicator of crop water stress severity,” Irrigation Science, vol. 24, no. 4, pp. 233–240, May 2006, doi: 10.1007/s00271-005-0022-8. [16] H. E. Jensen, H. Svendsen, S. E. Jensen, and V. O. Mogensen, “Canopy-air temperature of crops grown under different irrigation regimes in a temperate humid climate,” Irrigation Science, vol. 11, no. 3, pp. 181–188, Jul. 1990, doi: 10.1007/BF00189456. [17] R. Asati, M. K. Tripathi, S. Tiwari, R. K. Yadav, and N. Tripathi, “Molecular breeding and drought tolerance in chickpea,” Life, vol. 12, no. 11, p. 1846, Nov. 2022, doi: 10.3390/life12111846. [18] S. G. Fernandez et al., “Unmanned and autonomous ground vehicle,” International Journal of Electrical and Computer Engineering (IJECE), vol. 9, no. 5, pp. 4466-4472, Oct. 2019, doi: 10.11591/ijece.v9i5.pp4466-4472. [19] J. F. Kjelgaard, C. O. Stockle, and R. G. Evans, “Accuracy of canopy temperature energy balance for determining daily evapotranspiration,” Irrigation Science, vol. 16, no. 4, pp. 149–157, Jun. 1996, doi: 10.1007/BF02338965. [20] H. Lambers and R. S. Oliveira, Plant physiological ecology. Cham, NY: Springer International Publishing, 2019. [21] A. Rashid, J. C. Stark, A. Tanveer, and T. Mustafa, “Use of canopy temperature measurements as a screening tool for drought tolerance in spring wheat,” Journal of Agronomy and Crop Science, vol. 182, no. 4, pp. 231–238, May 1999, doi: 10.1046/j.1439- 037x.1999.00335.x. [22] M. P. Reynolds, C. S. Pierre, A. S. I. Saad, M. Vargas, and A. G. Condon, “Evaluating potential genetic gains in wheat associated with stress-adaptive trait expression in elite genetic resources under drought and heat stress,” Crop Science, vol. 47, no. SUPPL. DEC., p. S-172-S-189, Dec. 2007, doi: 10.2135/cropsci2007.10.0022IPBS. [23] R. Palanisamy, T. A. Singh, A. Ranjan, and J. Singh, “BLDC motor driven electric skateboard using SVPWM,” International Journal of Electrical and Computer Engineering (IJECE), vol. 10, no. 1, pp. 711-718, 2020, doi: 10.11591/ijece.v10i1.pp711-718. [24] D. F. Wanjura, D. R. Upchurch, and J. R. Mahan, “Behavior of temperature-based water stress indicators in BIOTIC-controlled irrigation,” Irrigation Science, vol. 24, no. 4, pp. 223–232, May 2006, doi: 10.1007/s00271-005-0021-9. [25] M. Balota, W. A. Payne, S. R. Evett, and T. R. Peters, “Morphological and physiological traits associated with canopy temperature depression in three closely related wheat lines,” Crop Science, vol. 48, no. 5, pp. 1897–1910, Sep. 2008, doi: 10.2135/cropsci2007.06.0317. [26] R. Palanisamy, S. Vidyasagar, V. Kalyanasundaram, and R. Sridhar, “Contactless digital tachometer using microcontroller,” International Journal of Electrical and Computer Engineering (IJECE), vol. 11, no. 1, pp. 293-299, Feb. 2021, doi: 10.11591/ijece.v11i1.pp293-299. BIOGRAPHIES OF AUTHORS Palanisamy Ramasamy received the bachelor of engineering degree in electrical and electronics engineering from Anna University, India, in 2011, and the masters of technology degree in power electronics and drives and the Ph.D. degree in power electronics from the SRM Institute of Science and Technology, Chennai, India, in 2013 and 2019, respectively. He is currently working as an assistant professor with the Department of Electrical Engineering, SRM Institute of Science and Technology. He has published more than 95 international and national journals. His research interests include power electronics multilevel inverters, various PWM techniques for power converters, FACTS controllers, and grid connected photovoltaic systems. He can be contacted at email: krspalani@gmail.com. Nagarajan Pandian received a bachelor of engineering degree in electronics and communication engineering from Anna University, Chennai, in 2007, a master of engineering degree in applied electronics from Anna University, Trichy in 2009, and a Ph.D. degree from Anna University, Chennai in 2015. He is currently working as an associate professor in the Department of Electronics and Communication Engineering at SRM Institute of Science and Technology, Vadapalani, Chennai, India. His research interests include FPGA implementation, low-power VLSI systems, device modeling, and VLSI architectures for image processing. He can be contacted at email: nagarajan.pandiyan@gmail.com.
  • 6.  ISSN: 2089-4864 Int J Reconfigurable & Embedded Syst, Vol. 13, No. 1, March 2024: 105-110 110 Krishnamurthy Mayathevar received the master of engineering and bachelor of engineering degrees from Anna University in 2008 and 2006, respectively, and has awarded doctorate during the year 2021 from Anna University. He is currently working as an assistant professor of Electronics and Communication Engineering Department, PSNA College of Engineering and Technology, Dindigul, India. He can be contacted at email: krishnamurthy184@gmail.com. Ramkumar Ravindran is currently working as an assistant professor in the Department of Electrical and Electronics Engineering at Dhanalakshmi Srinivasan University, Trichy. He obtained his Ph.D. under Faculty of Electrical Engineering from Anna University (2022), Chennai. He completed his master of engineering in Sethu Institute of Technology (2012), Madurai. He completed his bachelor of engineering in K.L.N. College of Information Technology (2008), Madurai. He has published more than 35 Scopus indexed journals and 6 SCI journals in his field. He has 11 years of teaching experience and 1-year industrial experience. His area of interest is power electronic converters, renewable energy and micro grid. He can be contacted at email: 2019ramkr@gmail.com. Srinivasa Rao Kandula is currently working as a professor in the Department of Electronics and Communication Engineering at Dhanekula Institute of Engineering and Technology, Ganguru, Vijayawada, Andhra Pradesh. He obtained his Ph.D. under the Department of Electronics and Communication Engineering from Jawaharlal Nehru Technological University Kakinada (2016), Kakinada. He completed his masters of technology in E.C.E from Jawaharlal Nehru Technological University Kakinada (2007), Kakinada. He completed his bachelor technology in E.C.E from Daita Mahdusudana Sastry Sri Venkateswara Hindu College of engineering (2002), Machilipatnam. He has 19 years of teaching experience and 1-year of Industrial experience. He has completed a LRDE funding consultancy project and he has published 15 peer reviewed journals in various International Journals. His area of interest is wireless communications, digital signal processing and IoT. He can be contacted at email: ksrinivas.ece@gmail.com. Selvabharathi Devadoss received bachelor of engineering degree in ECE from Valliammai Engineering College, affiliated to Anna University, Tamil Nadu, India in the 2007, and received the masters of technology degree in power electronics and drives from SRM University, Kattankulathur, Tamil Nadu, India in 2012. He is currently working as an assistant professor in EEE Department at SRM Institute of Science and Technology, Kattankulathur India. His research interest includes advancing the battery health management techniques for real time monitoring and diagnostics. He can be contacted at email: dsbsrm@gmail.com. Selvakumar Kuppusamy received bachelor of engineering degree in electrical and electronics engineering, master of engineering degree in power system engineering both from Anna University and received Ph.D. in deregulated power systems from SRM University, Kattankulathur, Tamil Nadu, India in 2018. He is currently working as an assistant professor in SRM University. His research interests include unit commitment, economic dispatch, power system optimization and smart grid, distributed generation in power system. He can be contacted at email: selvakse@gmail.com.