Analysis and experimental implementation of affordable smart irrigation system using IoT to reduce agricultural costs and minimize water usage

Abstract Smart irrigation systems utilising the Internet of Things (IoT) technology and sensory systems have emerged as a revolutionary approach to modernising agriculture and addressing sustainability challenges. The worldwide agricultural sector continues to struggle with two major problems, which include water resource depletion and high operational expenses because of outdated irrigation systems. The research investigates the immediate requirement for budget-friendly precision agriculture solutions that can serve small to medium farmers operating in limited resource areas. The paper describes the development of an affordable IoT-based smart irrigation system that underwent experimental testing. The system uses an ESP32 microcontroller as its core component while incorporating a capacitive soil moisture sensor for precise measurements, a DHT11 sensor for environmental data collection, and the Blynk IoT platform for live monitoring and distant system operation. The system begins irrigation when soil moisture reaches 20% and stops irrigation when moisture levels reach 80%. The system achieved operational success through field tests, which showed it used 25–35% less water than fixed-schedule irrigation systems while reducing operational expenses. The research proves that this affordable design can be duplicated and shows both technical and financial viability, which makes it an effective solution for sustainable farming practices.

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Publication Details

Journal
Applied Water Science
Published
2026-01-03
DOI
https://doi.org/10.1007/s13201-025-02727-4
Citations
1
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
31.34
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article

Analysis and experimental implementation of affordable smart irrigation system using IoT to reduce agricultural costs and minimize water usage

Mofreh A. Hashim, Enas E. Hussein, Sherif S. M. Ghoneim, Yousra Boukri et al.
1 citations
Applied Water Science
Smart Agriculture and AI
31.34
article

Analysis and experimental implementation of affordable smart irrigation system using IoT to reduce agricultural costs and minimize water usage

Mofreh A. Hashim, Enas E. Hussein, Sherif S. M. Ghoneim, Yousra Boukri, Prabhu Paramasivam, Rania Farah Mansour, Hazare Sonya Hamici, Alla Eddine Toubal Maamar
article en
1 citations

Abstract

Abstract Smart irrigation systems utilising the Internet of Things (IoT) technology and sensory systems have emerged as a revolutionary approach to modernising agriculture and addressing sustainability challenges. The worldwide agricultural sector continues to struggle with two major problems, which include water resource depletion and high operational expenses because of outdated irrigation systems. The research investigates the immediate requirement for budget-friendly precision agriculture solutions that can serve small to medium farmers operating in limited resource areas. The paper describes the development of an affordable IoT-based smart irrigation system that underwent experimental testing. The system uses an ESP32 microcontroller as its core component while incorporating a capacitive soil moisture sensor for precise measurements, a DHT11 sensor for environmental data collection, and the Blynk IoT platform for live monitoring and distant system operation. The system begins irrigation when soil moisture reaches 20% and stops irrigation when moisture levels reach 80%. The system achieved operational success through field tests, which showed it used 25–35% less water than fixed-schedule irrigation systems while reducing operational expenses. The research proves that this affordable design can be duplicated and shows both technical and financial viability, which makes it an effective solution for sustainable farming practices.

Applied Water ScienceVol. 16(2)
Taif University (SA), University of Boumerdes (DZ), Ethiopian Civil Service University (ET), National Water Research Center (EG), Chitkara University (IN)
Zero hunger
Openalex Percentile: Top 3%
Smart Agriculture and AI
31.34
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