Ontologies for Smart Agriculture: A Path Toward Explainable AI—A Systematic Literature Review
Smart agriculture has grown significantly over the last few years, particularly with the integration of advanced technologies (e.g., the Internet of Things, robots, artificial intelligence, etc.), leading to the development of intelligent agricultural systems. However, these systems often lack data...
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| Format: | Article |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10973055/ |
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| author | Rima Grati Najla Fattouch Khouloud Boukadi |
| author_facet | Rima Grati Najla Fattouch Khouloud Boukadi |
| author_sort | Rima Grati |
| collection | DOAJ |
| description | Smart agriculture has grown significantly over the last few years, particularly with the integration of advanced technologies (e.g., the Internet of Things, robots, artificial intelligence, etc.), leading to the development of intelligent agricultural systems. However, these systems often lack data integration, interoperability, and semantic explainability. Various approaches have been proposed to address these challenges. This study provides a comprehensive literature review that addresses, on the one hand, the use of semantic resources (e.g., semantic web technologies and ontologies) to tackle data integration and interoperability in smart agriculture systems and, on the other hand, the integration of explainable artificial intelligence into smart agricultural systems. Furthermore, it aims to identify limitations in existing studies and explore potential avenues for future research. This research introduces key concepts related to smart agriculture, semantic resources, and explainable artificial intelligence. Subsequently, three clusters of studies are presented, including semantic resources for smart agriculture, leveraging the explainable artificial intelligence for smart agriculture, and the role of semantic resources in the explainable artificial intelligence-based agriculture systems. Lastly, the limitations of the semantic-based smart agriculture system are examined, along with potential future research areas. |
| format | Article |
| id | doaj-art-b46b293cbafd4e4f82c89471b2f3c5aa |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-b46b293cbafd4e4f82c89471b2f3c5aa2025-08-20T03:52:25ZengIEEEIEEE Access2169-35362025-01-0113728837290510.1109/ACCESS.2025.356320210973055Ontologies for Smart Agriculture: A Path Toward Explainable AI—A Systematic Literature ReviewRima Grati0Najla Fattouch1https://orcid.org/0000-0003-4468-4929Khouloud Boukadi2College of Technological Technology, Zayed University, Abu Dhabi, United Arab EmiratesMiracl Laboratory, FSEG Sfax, University of Sfax, Sfax, TunisiaMiracl Laboratory, FSEG Sfax, University of Sfax, Sfax, TunisiaSmart agriculture has grown significantly over the last few years, particularly with the integration of advanced technologies (e.g., the Internet of Things, robots, artificial intelligence, etc.), leading to the development of intelligent agricultural systems. However, these systems often lack data integration, interoperability, and semantic explainability. Various approaches have been proposed to address these challenges. This study provides a comprehensive literature review that addresses, on the one hand, the use of semantic resources (e.g., semantic web technologies and ontologies) to tackle data integration and interoperability in smart agriculture systems and, on the other hand, the integration of explainable artificial intelligence into smart agricultural systems. Furthermore, it aims to identify limitations in existing studies and explore potential avenues for future research. This research introduces key concepts related to smart agriculture, semantic resources, and explainable artificial intelligence. Subsequently, three clusters of studies are presented, including semantic resources for smart agriculture, leveraging the explainable artificial intelligence for smart agriculture, and the role of semantic resources in the explainable artificial intelligence-based agriculture systems. Lastly, the limitations of the semantic-based smart agriculture system are examined, along with potential future research areas.https://ieeexplore.ieee.org/document/10973055/Explainable AIontologiessemantic explainable AIsemantic resources |
| spellingShingle | Rima Grati Najla Fattouch Khouloud Boukadi Ontologies for Smart Agriculture: A Path Toward Explainable AI—A Systematic Literature Review IEEE Access Explainable AI ontologies semantic explainable AI semantic resources |
| title | Ontologies for Smart Agriculture: A Path Toward Explainable AI—A Systematic Literature Review |
| title_full | Ontologies for Smart Agriculture: A Path Toward Explainable AI—A Systematic Literature Review |
| title_fullStr | Ontologies for Smart Agriculture: A Path Toward Explainable AI—A Systematic Literature Review |
| title_full_unstemmed | Ontologies for Smart Agriculture: A Path Toward Explainable AI—A Systematic Literature Review |
| title_short | Ontologies for Smart Agriculture: A Path Toward Explainable AI—A Systematic Literature Review |
| title_sort | ontologies for smart agriculture a path toward explainable ai x2014 a systematic literature review |
| topic | Explainable AI ontologies semantic explainable AI semantic resources |
| url | https://ieeexplore.ieee.org/document/10973055/ |
| work_keys_str_mv | AT rimagrati ontologiesforsmartagricultureapathtowardexplainableaix2014asystematicliteraturereview AT najlafattouch ontologiesforsmartagricultureapathtowardexplainableaix2014asystematicliteraturereview AT khouloudboukadi ontologiesforsmartagricultureapathtowardexplainableaix2014asystematicliteraturereview |