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This study examines the benefits and uses of Industry 4.0 technologies in horticulture for real-time monitoring of fruit and vegetable conditions for growth and disease estimation. The study also addresses the challenges faced in horticulture and provides recommendations for the widespread adoption of AI-based IoT systems and blockchain supply chain integration. The methodology used in the study combines computer vision with distributed deep learning techniques in order to identify fruits and vegetables by their shape. Finally, the study identifies limitations and provides recommendations for future work.

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Decision Making Process for a Sustainable Horticulture Using AI

  • 会议论文

  • 发表日期：

    2025年

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  • Costin Lianu,
  • Cezar Braicu,
  • Radu Bucea-Manea-Tonis

摘要

This study examines the benefits and uses of Industry 4.0 technologies in horticulture for real-time monitoring of fruit and vegetable conditions for growth and disease estimation. The study also addresses the challenges faced in horticulture and provides recommendations for the widespread adoption of AI-based IoT systems and blockchain supply chain integration. The methodology used in the study combines computer vision with distributed deep learning techniques in order to identify fruits and vegetables by their shape. Finally, the study identifies limitations and provides recommendations for future work.