Optimizing AI Algorithms for the SmartHydro System to Enhance Crop Yields Across Diverse South African Climates
Domain:
agricultureCreator:
Han
Publisher:
DMP
Host:
This research proposes the optimization of AI algorithms within the SmartHydro system—an AI- and IoT-enabled hydroponic farming platform—to address crop yield inconsistencies experienced by subsistence farmers across diverse South African climates. While hydroponics offers a sustainable solution to water scarcity and soil degradation, regional variations in water quality and environmental conditions affect nutrient uptake, leading to inconsistent yields. The study aims to develop a Reinforcement Learning model, supported by Fuzzy Logic, to dynamically adjust pH and electrical conductivity based on real-time, location-specific data. Employing a mixed-methods approach, the research will evaluate the technical effectiveness of the optimized system and assess its socio-economic impact on rural subsistence farmers, particularly women. The expected outcome is a more resilient and accessible hydroponic system that enhances food security and economic stability in resource-constrained communities.
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