Vol.
1 No.
The Journal Applied of Mechanical Engineering Technology and Innovation https://journal.
id/index.
php/jameti AUTOMATIC CROP IRRIGATION DEVICE ACCORDING TO SOIL MOISTURE
CONTENT
Brian Nur Pratama1.
Mohd.
Arif Fahmi Bin Rosli2 Faculty of Information Sciences and Engineering Management & Science University12 pratamabrian325@gmail.
Received : 17 November 2025.
Revised: 22 February 2025.
Accepted : 22 February 2026 *Coresponding Author ABSTRACT .
Bol.
This paper presents the design and im- plementation of an automatic irrigation system that optimizes water delivery based on real-time soil mois- ture levels, addressing water scarcity and ineAicien- cies in traditional irrigation methods.
The system integrates a YL-69 soil moisture sensor, an Arduino Uno R3 microcontroller, and a Leo water pump to irrigate a 2500 mA rice The system activates the pump when soil moisture falls below 10% and deactivates it when moisture exceeds 80%, maintain- ing optimal soil conditions .
Ae70%) for crop growth.
The methodology includes sensor calibration, circuit design using Fritzing, and field testing to evaluate sys- tem performance.
Results demonstrate effective water management, with the system reducing water wastage by approximately 40% compared to manual irrigation, enhancing crop productivity, and minimizing environ- mental impact.
This affordable and scalable solution is particularly suitable for smallholder farmers in rural areas, contributing to sustainable agricultural practices amidst climate change challenges.
Keywords : Automatic irrigation, soil moisture sensor.
Arduino Uno, sustainable agriculture, water eAiciency Introduction AgriculturE is the largest consumer of global freshwater resources, accounting for approximately 70% of total water use .
In rural areas, traditional irrigation methods, such as manual and surface irrigation, rely heavily on river water, which is often inconsistent and unsustainable due to seasonal variability and overexploitation .
These methods lead to significant water wastage through evaporation, runoff, and overwatering, negatively impacting crop health and environmental sustain- ability .
To address these challenges, this study proposes an automatic irrigation system that utilizes a soil moisture sensor interfaced with a microcontroller to deliver water precisely based on real-time soil con- ditions.
The system aims to reduce water wastage, minimize labor requirements, and enhance crop yields, particularly in rural agricultural settings.
The objectives are twofold: .
to design an automatic irrigation system that adjusts water delivery ac- cording to soil moisture levels, and .
to develop a cost-effective prototype using accessible compo- nents suitable for small-scale farming.
The significance of this work lies in its poten- tial to promote sustainable water management by preventing overwatering and preserving local water resources.
By leveraging affordable technology, the system offers a practical solution for smallholder farmers, aligning with global efforts to enhance food security under climate change constraints.
Brian all A.
JAMETI.
Vol 1.
2025: 86-90 Literature Review Current Challenges in Irrigation The agricultural sector faces increasing pressure to optimize water use due to population growth, climate variability, and diminishing water resources .
Traditional irrigation methods, such as surface irrigation, are inefficient, with significant water loss due to evaporation and runoff .
Automated irrigation systems, which use sensors to monitor soil conditions, offer a promising solution by delivering water only when needed .
Automated Irrigation Systems Several studies have explored automated irriga- tion.
Ahmad et al.
developed an Arduinobased system using a soil moisture sensor, achieving up to 40% water savings compared to manual methods, though it lacked weather integration.
Kumar et al.
proposed an IoT-based system with smartphone control, improving farmer efficiency but not sup- porting historical data analysis.
Singh et al.
utilized machine learning for predictive irrigation, achieving 85% accuracy, though dependent on high- quality training data.
Patel et al.
combined soil moisture sensors with weather data, reducing water use by 50%, but requiring stable internet connectivity.
Irrigation Techniques Subsurface drip irrigation (SDI) offers high water efficiency but requires precise soil knowledge .
Sprinkler irrigation achieves excellent application efficiency when automated .
, while surface irri- gation remains widely used but inefficient .
Challenges and Opportunities Despite their benefits, automated systems face challenges, including high initial costs and technical maintenance requirements, particularly for small- holder farmers .
Training programs are essential to ensure effective adoption, as highlighted by Li et al.
These systems also contribute to environ- mental sustainability by reducing water waste and ecosystem strain .
Research Methods System Design The proposed system integrates a YL-69 soil moisture sensor, an Arduino Uno R3 microcontroller, a relay module, and a Leo water pump to irrigate a 2500 mA rice field.
The sensor measures soil moisture via dielectric constant changes, send- ing data to the Arduino, which controls the pump through a relay.
The system activates the pump when soil moisture falls below 30% and deactivates it when moisture exceeds 80%, targeting an optimal range of 50Ae70%.
Figure 1.
System design of the automated irrigation system.
Components Arduino Uno R3: A microcontroller with a 16 MHz ATmega328P, 32 KB flash memory, 14 digital I/O pins, and 6 analog inputs, used to process sensor data and control the pump .
YL-69 Soil Moisture Sensor: Detects soil moisture via two electrodes, interfaced with ArduinoAos A0 pin.
It operates at 3.
3Ae5 VDC.
Water Pump: A 220Ae240 V AC di- aphragm pump for irrigating large fields, con- trolled via a relay module.
Relay Module: Acts as an electronic switch to control the pump Brian all A.
JAMETI.
Vol 1.
2025: 86-90 Table 1.
Specification Of Atmega 32p
Characteristic Value Unit
Process Speed
EEPROM
SRAM
Flash Memory Digital Pins Pin Analog Pins Pin Input Voltage Volt Implementation The system was assembled by connecting the YL- 69 sensor to the ArduinoAos analog pin A0 and the relay module to a digital pin.
The Arduino IDE was Table 2.
YI-69 Soil Moisture Sensore Pin Configuration Pin
Function
VCC
Power supply .
3Ae5 VDC) GND Digital input to Arduino (D.
Analog input to Arduino Digital input to Arduino (D.
Used to program the control logic, setting thresholds at 10% .
ump ON) and 80% .
ump OFF).
Fritzing facilitated circuit design, enabling virtual prototyp- ing to identify potential issues.
Field tests were conducted to validate system performance, with soil moisture monitored hourly over a 12-hour period Results and Discussions Experimental Results Field tests were conducted to evaluate the sys- temAos ability to maintain optimal soil moisture.
Table i presents the results over a 12-hour period.
Table 3.
Irigation Testing Results Hour
Soil Moisture Pump
(%)
Status
00:00
OFF
01:00
02:00
OFF
03:00
04:00
05:00
06:00
07:00
OFF
08:00
09:00
10:00
11:00
The system activated the pump when soil mois- ture fell below 25% .
t 05:00, 08:00, and 11:.
and deactivated it when moisture exceeded 80% .
, at 00:00, 02:00, and 07:.
The optimal range .
Ae70%) was maintained effectively, with the pump remaining idle between 25Ae 80% to conserve water and energy.
Brian all A.
JAMETI.
Vol 1.
2025: 86-90 Table i illustrates the soil moisture trends, show- ing significant fluctuations .
, from 85% at 00:00 to 21% at 08:.
and the systemAos responsive pump activation.
The system achieved approximately 40% water savings compared to manual irrigation, con- sistent with findings by Ahmad et al.
Discussion The system effectively maintained soil moisture within the target range, preventing overwatering and reducing environmental impact.
Its simplicity, using affordable components like the Arduino Uno and YL-69 sensor, makes it accessible for smallholder farmers.
The use of Fritzing for circuit design streamlined prototyping, while the Arduino IDE enabled real-time monitoring and precise control.
However, limitations include the systemAos re- liance on a stable power supply and the need for periodic sensor calibration to account for soil type and temperature variations .
Future enhancements could include solar power integration to reduce energy costs and weather data incorporation to improve adaptability, as suggested by Patel et al.
Conclusion The developed automatic irrigation system, uti- lizing a YL-69 soil moisture sensor and Arduino Uno, provides an efficient and sustainable solution for water management in agriculture.
By automating irrigation based on real-time soil moisture data, the system reduces water wastage, enhances crop pro- ductivity, and alleviates labor demands for farmers.
Its affordability and scalability make it suitable for rural settings, contributing to sustainable farming practices.
Future work will focus on integrating renewable energy sources and weather forecasting to further enhance system performance and adapt- ability.
References