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Data Management and Integration of Low Power Consumption Embedded Devices IoT for Transforming Smart Agriculture into Actionable Knowledge

Author

Listed:
  • El Mehdi Ouafiq

    (Hassania School of Public Works, Km 7 Rte d’El Jadida, Casablanca BP 8108, Morocco)

  • Rachid Saadane

    (Hassania School of Public Works, Km 7 Rte d’El Jadida, Casablanca BP 8108, Morocco)

  • Abdellah Chehri

    (Department of Applied Sciences, University of Quebec in Chicoutimi, 555 Bd de l’Université, Chicoutimi, QC G7H 2B1, Canada)

Abstract

Smart agriculture today uses a wide range of wireless communication technologies. Low Power Consumption Embedded Devices (LPCED), such as the Internet of Things (IoT) and Wireless Sensor Networks, make it possible to work over great distances at a reduced cost but with limited transferable data volumes. However, data management (DM) in intelligent agriculture is still not well understood due to the fact that there are not enough scientific publications available on this. Though data management (DM) benefits are factual and substantial, many challenges must be addressed in order to fully realize the DM’s potential. The main difficulties are data integration complexities, the lack of skilled personnel and sufficient resources, inadequate infrastructure, and insignificant data warehouse architecture. This work proposes a comprehensive architecture that includes big data technologies, IoT components, and knowledge-based systems. We proposed an AI-based architecture for smart farming. This architecture called, Smart Farming Oriented Big-Data Architecture (SFOBA), is designed to guarantee the system’s durability and the data modeling in order to transform the business needs for smart farming into analytics. Furthermore, the proposed solution is built on a pre-defined big data architecture that includes an abstraction layer of the data lake that handles data quality, following a data migration strategy in order to ensure the data’s insights.

Suggested Citation

  • El Mehdi Ouafiq & Rachid Saadane & Abdellah Chehri, 2022. "Data Management and Integration of Low Power Consumption Embedded Devices IoT for Transforming Smart Agriculture into Actionable Knowledge," Agriculture, MDPI, vol. 12(3), pages 1-16, February.
    • Handle: RePEc:gam:jagris:v:12:y:2022:i:3:p:329-:d:757734
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    References listed on IDEAS

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    1. Eduardo A. Haddad & Fatima Ezzahra Mengoub & Vinicius A. Vale, 2020. "Water content in trade: a regional analysis for Morocco," Economic Systems Research, Taylor & Francis Journals, vol. 32(4), pages 565-584, October.
    2. Faye Duchin & Carlos López-Morales, 2012. "Do Water-Rich Regions Have A Comparative Advantage In Food Production? Improving The Representation Of Water For Agriculture In Economic Models," Economic Systems Research, Taylor & Francis Journals, vol. 24(4), pages 371-389, July.
    3. Wolfert, Sjaak & Ge, Lan & Verdouw, Cor & Bogaardt, Marc-Jeroen, 2017. "Big Data in Smart Farming – A review," Agricultural Systems, Elsevier, vol. 153(C), pages 69-80.
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