Greenhouses have played an integral role in modern agriculture, providing controlled environments that optimize crop growth and extend growing seasons. However, despite their importance, there is a significant lack of accessible information, making it difficult for practitioners to achieve optimal cultivation or even get started. To address this gap, our work aims to develop a comprehensive ontology that encapsulates various aspects of greenhouse. This includes greenhouse specifications, cultivation practices, pest management, disease diagnosis and treatment, and environmental control. The ontology provides a structured framework that integrates and organizes knowledge about greenhouse farming, facilitating easier access and better decision-making. This paper presents our greenhouse modular ontology as well as the validation and evaluation process. The results obtained show that our solution can detect the appropriate stage or crop from different data sources and provide significant decision support.

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AIOGO: A Modular Ontology for Managing Greenhouses

  • Christine Lahoud,
  • Mariam Gawich,
  • Hajer Baazaoui,
  • Ihab Jomaa

摘要

Greenhouses have played an integral role in modern agriculture, providing controlled environments that optimize crop growth and extend growing seasons. However, despite their importance, there is a significant lack of accessible information, making it difficult for practitioners to achieve optimal cultivation or even get started. To address this gap, our work aims to develop a comprehensive ontology that encapsulates various aspects of greenhouse. This includes greenhouse specifications, cultivation practices, pest management, disease diagnosis and treatment, and environmental control. The ontology provides a structured framework that integrates and organizes knowledge about greenhouse farming, facilitating easier access and better decision-making. This paper presents our greenhouse modular ontology as well as the validation and evaluation process. The results obtained show that our solution can detect the appropriate stage or crop from different data sources and provide significant decision support.