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.
Authors
- Ziyou Mei
- Guchuan Zhu (ORCID: https://orcid.org/0000-0003-2117-6796)
- Jietao Dai
- Zian Wang (ORCID: https://orcid.org/0009-0004-1827-8999)
- Ruizhi Tang (ORCID: https://orcid.org/0000-0001-6512-845X)
- Hao Hu (ORCID: https://orcid.org/0000-0002-0614-3921)
- Jiahao Li (ORCID: https://orcid.org/0009-0002-7881-0647)
- Hai Lin
Institutions
- Guangzhou University (CN)
- South China University of Technology (CN)
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
- Guangzhou University