Optimization of the Irrigation Systems to Improve Crop Production in Sahelian Zones Using Microcontroller Systems

This paper is based on the use of microcontroller systems to help optimize irrigation systems in order to improve crop production in Sahelian zones. In this paper, we implement an automatic device using sensors to monitor environmental data such as soil and air conditions in real time, microcontrollers to make irrigation decisions based on these data, and modules to store data from the sensors. Analysis of this data enables informed irrigation and crop management decisions to be made. This approach enables efficient irrigation management by precisely adjusting the amount of water supplied to crops, minimizing human intervention and thus reducing costs and environmental impacts while maximizing crop yields. The results obtained in this study show that the system works well, and justify the possibility of adjusting system parameters according to crop type.

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Publication Details

Journal
Analecta Technica Szegedinensia
Published
2025-10-28
DOI
https://doi.org/10.14232/analecta.2025.2.34-45
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
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article

Optimization of the Irrigation Systems to Improve Crop Production in Sahelian Zones Using Microcontroller Systems

Jacob Mbarndouka Taamté, Patrick Dany Bavoua Kenfack, Albert Vandai Stanga
Analecta Technica Szegedinensia
Smart Agriculture and AI
article

Optimization of the Irrigation Systems to Improve Crop Production in Sahelian Zones Using Microcontroller Systems

Jacob Mbarndouka Taamté, Patrick Dany Bavoua Kenfack, Albert Vandai Stanga
article en

Abstract

This paper is based on the use of microcontroller systems to help optimize irrigation systems in order to improve crop production in Sahelian zones. In this paper, we implement an automatic device using sensors to monitor environmental data such as soil and air conditions in real time, microcontrollers to make irrigation decisions based on these data, and modules to store data from the sensors. Analysis of this data enables informed irrigation and crop management decisions to be made. This approach enables efficient irrigation management by precisely adjusting the amount of water supplied to crops, minimizing human intervention and thus reducing costs and environmental impacts while maximizing crop yields. The results obtained in this study show that the system works well, and justify the possibility of adjusting system parameters according to crop type.

Analecta Technica SzegedinensiaVol. 19(2)
Université de Yaoundé I (CM), Institut de Recherches Géologiques et Minières (CM)
Openalex Percentile: Top 77%
Smart Agriculture and AI
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