Optimizing Agriculture Water Use with Arduino Based IOT Smart Irrigation

In India, approximately 70% of the population relies on water-based occupations, predominantly agriculture, which consumes around 78–80% of the country’s water resources. Despite receiving nearly 4,000 billion cubic meters (BCM) of rainfall annually, the nation faces water scarcity due to uneven distribution and inefficient usage. With a growing population, effective water management has become crucial. This paper presents a smart irrigation system designed to optimize water use in agriculture. Traditional irrigation methods often result in water wastage and crop damage due to overwatering. The proposed system automates irrigation by utilizing an Arduino board, a soil moisture sensor, and a relay module, responding dynamically to real-time soil conditions. The Arduino microcontroller receives data from the soil moisture sensor, which continuously gauges the soil's moisture content. The Arduino uses a relay module to automatically turn on the water pump when the moisture level surpasses 450, a sign of dryness. Until the moisture level falls below 450, irrigation continues; after that, the pump is automatically shut off. Users can only view real time soil conditions and system status through the connected application interface the entire process is automated. Powered by solar panels, the system is energy-efficient and environmentally friendly. By delivering water precisely when needed, it reduces manual intervention and enhances crop health. The implementation of this smart irrigation system has demonstrated a reduction in water wastage by over 97% while significantly improving crop productivity.

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Publication Details

Journal
International Journal of Scientific Research in Science Engineering and Technology
Published
2025-09-25
DOI
https://doi.org/10.32628/ijsrset251368
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
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article

Optimizing Agriculture Water Use with Arduino Based IOT Smart Irrigation

H. K. Patel, Khushboo Shah, S. Mehta
International Journal of Scientific Research in Science Engineering and Technology
Smart Agriculture and AI
article

Optimizing Agriculture Water Use with Arduino Based IOT Smart Irrigation

H. K. Patel, Khushboo Shah, S. Mehta
article en

Abstract

In India, approximately 70% of the population relies on water-based occupations, predominantly agriculture, which consumes around 78–80% of the country’s water resources. Despite receiving nearly 4,000 billion cubic meters (BCM) of rainfall annually, the nation faces water scarcity due to uneven distribution and inefficient usage. With a growing population, effective water management has become crucial. This paper presents a smart irrigation system designed to optimize water use in agriculture. Traditional irrigation methods often result in water wastage and crop damage due to overwatering. The proposed system automates irrigation by utilizing an Arduino board, a soil moisture sensor, and a relay module, responding dynamically to real-time soil conditions. The Arduino microcontroller receives data from the soil moisture sensor, which continuously gauges the soil's moisture content. The Arduino uses a relay module to automatically turn on the water pump when the moisture level surpasses 450, a sign of dryness. Until the moisture level falls below 450, irrigation continues; after that, the pump is automatically shut off. Users can only view real time soil conditions and system status through the connected application interface the entire process is automated. Powered by solar panels, the system is energy-efficient and environmentally friendly. By delivering water precisely when needed, it reduces manual intervention and enhances crop health. The implementation of this smart irrigation system has demonstrated a reduction in water wastage by over 97% while significantly improving crop productivity.

International Journal of Scientific Research in Science Engineering and TechnologyVol. 12(5)
St Xavier’s College (IN)
Openalex Percentile: Top 80%
Smart Agriculture and AI
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