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IoT and Computer Vision in Smart Irrigation: A Review of Cost-Effective Solutions and Future Trends

Publié
Serveur de preprints
Preprints.org
DOI
10.20944/preprints202509.0128.v1

With an increase in pressure on global food systems and the growing scarcity of freshwater, smart irrigation powered by the Internet of Things (IoT) and Computer Vision (CV) presents a promising solution to sustainable agriculture. This paper provides a comprehensive review of scalable and cost-effective smart irrigation systems, analyzing over 20 recent studies to highlight the integration of sensors, microcontrollers, wireless technologies, and artificial intelligence. The synthesis of existing research demonstrates remarkable advancements, with systems achieving up to 85% in water savings, 92% in irrigation scheduling accuracy, and significant enhancements in crop yields. Furthermore, the analysis covers real-time soil and climate data monitoring, image-based crop health assessment, and intelligent decision support systems, underscoring the feasibility of solutions costing less than $50. Key challenges, including energy consumption, connectivity, and rural deployment, are also discussed, providing a robust foundation for future research in precision agriculture.

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