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Extending ONTAgri with Service-Oriented Architecture towards Precision Farming Application

Author

Listed:
  • Muhammad Fahad

    (Faculty of Engineering Sciences & Technology, Hamdard University, Karachi 74600, Pakistan
    College of Computing and Information Science, Pakistan Air Force, Karachi Institute of Economics and Technology, Karachi 75190, Pakistan)

  • Tariq Javid

    (Faculty of Engineering Sciences & Technology, Hamdard University, Karachi 74600, Pakistan)

  • Hira Beenish

    (College of Computing and Information Science, Pakistan Air Force, Karachi Institute of Economics and Technology, Karachi 75190, Pakistan)

  • Adnan Ahmed Siddiqui

    (Faculty of Engineering Sciences & Technology, Hamdard University, Karachi 74600, Pakistan)

  • Ghufran Ahmed

    (School of Computing, National University of Computer and Engineering Science (FAST-NUCES), Karachi 75030, Pakistan)

Abstract

The computer science perspective of ontology refers to ontology as a technology, however, with a different perspective in terms of interrogations and concentrations to construct engineering models of reality. Agriculture-centered architectures are among rich sources of knowledge that are developed, preserved, and released for farmers and agro professionals. Many researchers have developed different variants of existing ontology-based information systems. These systems are primarily picked agriculture-related ontological strategies based on activities such as crops, weeds, implantation, irrigation, and planting, to name a few. By considering the limitations on agricultural resources in the ONTAgri scenario, in this paper, an extension of ontology is proposed. The extended ONTAgri is a service-oriented architecture that connects precision farming with both local and global decision-making methods. These decision-making methods are connected with the Internet of Things systems in parallel for the input processing of system ontology. The proposed architecture fulfills the requirements of Agriculture 4.0. The significance of the proposed approach aiming to solve a multitude of agricultural problems being faced by the farmers is successfully demonstrated through SPARQL queries.

Suggested Citation

  • Muhammad Fahad & Tariq Javid & Hira Beenish & Adnan Ahmed Siddiqui & Ghufran Ahmed, 2021. "Extending ONTAgri with Service-Oriented Architecture towards Precision Farming Application," Sustainability, MDPI, vol. 13(17), pages 1-14, August.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:17:p:9801-:d:626645
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    References listed on IDEAS

    as
    1. Anat Goldstein & Lior Fink & Gilad Ravid, 2021. "A Framework for Evaluating Agricultural Ontologies," Sustainability, MDPI, vol. 13(11), pages 1-12, June.
    2. Xue-Bo Jin & Xing-Hong Yu & Xiao-Yi Wang & Yu-Ting Bai & Ting-Li Su & Jian-Lei Kong, 2020. "Deep Learning Predictor for Sustainable Precision Agriculture Based on Internet of Things System," Sustainability, MDPI, vol. 12(4), pages 1-18, February.
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    Citations

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    Cited by:

    1. Muhammad Fahad & Tariq Javid & Hira Beenish, 2022. "Service oriented Architecture for Agriculture System Integration with Ontology," International Journal of Innovations in Science & Technology, 50sea, vol. 4(3), pages 880-890, July.
    2. Jaroslav Vrchota & Martin Pech & Ivona Švepešová, 2022. "Precision Agriculture Technologies for Crop and Livestock Production in the Czech Republic," Agriculture, MDPI, vol. 12(8), pages 1-18, July.

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