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This study investigates the integration of Artificial Intelligence (AI) and the Internet of Things (IoT), known as the Artificial Intelligence of Things (AIoT), for smart greenhouse management. A fine-tuned YOLOv8 deep learning model was employed to simultaneously detect Cucumis melo L. and determine its growth stages under varying environmental conditions. The model was trained on a diverse dataset captured by an IoT-based camera system and achieved high accuracy, with a mean Average Precision (mAP@0.5) of 0.959 and an F1-score of 0.92. Additionally, a smart drip irrigation control system was developed, consisting of hardware, a mobile application, and a web-based cloud platform, to optimize water usage and support real-time monitoring and data management in Cucumis melo L. cultivation.

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Application of Artificial Intelligence and IoT in Determining Growth Stages and Automatically Providing Fertilization for Cucumis melo L. in Greenhouses

  • 会议论文

  • 发表日期：

    2026年

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  • Minh-Dung Lam,
  • Quoc-Bao Trương,
  • Hong-Nhung Le Thi,
  • Tan-Kiet Nguyen Thanh

摘要

This study investigates the integration of Artificial Intelligence (AI) and the Internet of Things (IoT), known as the Artificial Intelligence of Things (AIoT), for smart greenhouse management. A fine-tuned YOLOv8 deep learning model was employed to simultaneously detect Cucumis melo L. and determine its growth stages under varying environmental conditions. The model was trained on a diverse dataset captured by an IoT-based camera system and achieved high accuracy, with a mean Average Precision (mAP@0.5) of 0.959 and an F1-score of 0.92. Additionally, a smart drip irrigation control system was developed, consisting of hardware, a mobile application, and a web-based cloud platform, to optimize water usage and support real-time monitoring and data management in Cucumis melo L. cultivation.