Design and Implementation of an Autonomous Intelligent Fertigation System for Cross-Regional Applications

Conventional fertigation systems suffer from limited cross-regional adaptability, mainly due to unstable fertilizer flow from fixed-aperture units, poor terrain adaptability, and an inadequate response to environmental heterogeneity. This study proposes an autonomous, cross-regional intelligent fertigation system based on an STM32F1 microcontroller and UART communication protocols. The system integrates a mechanically adjustable iris fertilizer delivery unit, a dual-axis fertigation module, a data interconnection unit, and comprehensive control software with dynamic calibration capabilities. Prototype evaluations conducted on both sloped terrain (up to 38°) and flat surfaces demonstrate a stable performance, achieving fertilizer flow control errors below 3%, irrigation deviation under 5%, and fertilization deviation within 2%. Real-time data acquisition, remote monitoring, and intelligent operation are supported by a YOLOv5s-based visual recognition system, which attains an [email protected] of 92.5%. This integrated solution offers a robust approach to precision agriculture across diverse environmental conditions.

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Publication Details

Journal
Actuators
Published
2025-08-22
DOI
https://doi.org/10.3390/act14090413
Citations
1
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
1.75

Funders

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article

Design and Implementation of an Autonomous Intelligent Fertigation System for Cross-Regional Applications

Ziyou Mei, Guchuan Zhu, Jietao Dai, Zian Wang et al.
1 citations
Actuators
Smart Agriculture and AI
1.75
article

Design and Implementation of an Autonomous Intelligent Fertigation System for Cross-Regional Applications

Ziyou Mei, Guchuan Zhu, Jietao Dai, Zian Wang, Ruizhi Tang, Hao Hu, Jiahao Li, Hai Lin
article en
1 citations

Abstract

Conventional fertigation systems suffer from limited cross-regional adaptability, mainly due to unstable fertilizer flow from fixed-aperture units, poor terrain adaptability, and an inadequate response to environmental heterogeneity. This study proposes an autonomous, cross-regional intelligent fertigation system based on an STM32F1 microcontroller and UART communication protocols. The system integrates a mechanically adjustable iris fertilizer delivery unit, a dual-axis fertigation module, a data interconnection unit, and comprehensive control software with dynamic calibration capabilities. Prototype evaluations conducted on both sloped terrain (up to 38°) and flat surfaces demonstrate a stable performance, achieving fertilizer flow control errors below 3%, irrigation deviation under 5%, and fertilization deviation within 2%. Real-time data acquisition, remote monitoring, and intelligent operation are supported by a YOLOv5s-based visual recognition system, which attains an [email protected] of 92.5%. This integrated solution offers a robust approach to precision agriculture across diverse environmental conditions.

ActuatorsVol. 14(9)
Guangzhou University (CN), South China University of Technology (CN)
Guangzhou University
Openalex Percentile: Top 13%
Smart Agriculture and AI
1.75
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Design and Implementation of an Autonomous Intelligent Fertigation System for Cross-Regional Applications — Ziyou Mei, Guchuan Zhu, et al. · Actuators (2025) | TGRS Research Map | TGRS