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The Effects of AI-Supported Autonomous Irrigation Systems on Water Efficiency and Plant Quality: A Case Study of
Gülcay Ercan Oğuztürk1, Caner Murat2, Meryem Yurtseven1
1Department of Landscape Architecture, Recep Tayyip Erdoğan University, Rize 53020, Türkiye.
Abstract:
This study investigates the effects of an AI-supported irrigation system on the production of natural plant species and irrigation efficiency at Rize Recep Tayyip Erdoğan University. To enhance water resource efficiency while utilizing Turkey's rich plant diversity, Geranium psilostemon Ledeb. (Black-Eyed Crane's-Bill) was selected for cultivation. The research includes adaptation trials and growth monitoring of this perennial taxon, which naturally grows at an altitude of 2000 m. The experiments were conducted in two different environments: one utilizing an AI-supported irrigation system and the other relying on manual irrigation. The findings reveal that AI-supported irrigation systems optimize irrigation strategies, providing a more efficient and effective plant cultivation process compared to manual irrigation. The AI-supported irrigation system continuously monitors air and soil moisture levels, ensuring optimal irrigation conditions and instant adaptation to seasonal variations. This innovative approach minimizes water losses while preventing soil salinization, thereby offering a significant solution for sustainable agricultural practices. In conclusion, this study demonstrates that natural plant species can be effectively cultivated using AI-supported irrigation systems and that these systems hold great potential for water conservation and ecological balance. These findings present a crucial step toward developing effective solutions for global water challenges and promoting sustainable landscape and agricultural practices.
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