Data Management and Integration of Low Power Consumption Embedded Devices IoT for Transforming Smart Agriculture into Actionable Knowledge
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 volu...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Agriculture |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2077-0472/12/3/329 |
| _version_ | 1797447401490874368 |
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| author | El Mehdi Ouafiq Rachid Saadane Abdellah Chehri |
| author_facet | El Mehdi Ouafiq Rachid Saadane Abdellah Chehri |
| author_sort | El Mehdi Ouafiq |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-09T13:55:07Z |
| format | Article |
| id | doaj.art-848f05497a1f42ce9431d77f9460c6f5 |
| institution | Directory Open Access Journal |
| issn | 2077-0472 |
| language | English |
| last_indexed | 2024-03-09T13:55:07Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agriculture |
| spelling | doaj.art-848f05497a1f42ce9431d77f9460c6f52023-11-30T20:43:02ZengMDPI AGAgriculture2077-04722022-02-0112332910.3390/agriculture12030329Data Management and Integration of Low Power Consumption Embedded Devices IoT for Transforming Smart Agriculture into Actionable KnowledgeEl Mehdi Ouafiq0Rachid Saadane1Abdellah Chehri2Hassania School of Public Works, Km 7 Rte d’El Jadida, Casablanca BP 8108, MoroccoHassania School of Public Works, Km 7 Rte d’El Jadida, Casablanca BP 8108, MoroccoDepartment of Applied Sciences, University of Quebec in Chicoutimi, 555 Bd de l’Université, Chicoutimi, QC G7H 2B1, CanadaSmart 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.https://www.mdpi.com/2077-0472/12/3/329smart farmingLow Power Consumption Embedded DevicesIoTdata managementsustainability |
| spellingShingle | El Mehdi Ouafiq Rachid Saadane Abdellah Chehri Data Management and Integration of Low Power Consumption Embedded Devices IoT for Transforming Smart Agriculture into Actionable Knowledge Agriculture smart farming Low Power Consumption Embedded Devices IoT data management sustainability |
| title | Data Management and Integration of Low Power Consumption Embedded Devices IoT for Transforming Smart Agriculture into Actionable Knowledge |
| title_full | Data Management and Integration of Low Power Consumption Embedded Devices IoT for Transforming Smart Agriculture into Actionable Knowledge |
| title_fullStr | Data Management and Integration of Low Power Consumption Embedded Devices IoT for Transforming Smart Agriculture into Actionable Knowledge |
| title_full_unstemmed | Data Management and Integration of Low Power Consumption Embedded Devices IoT for Transforming Smart Agriculture into Actionable Knowledge |
| title_short | Data Management and Integration of Low Power Consumption Embedded Devices IoT for Transforming Smart Agriculture into Actionable Knowledge |
| title_sort | data management and integration of low power consumption embedded devices iot for transforming smart agriculture into actionable knowledge |
| topic | smart farming Low Power Consumption Embedded Devices IoT data management sustainability |
| url | https://www.mdpi.com/2077-0472/12/3/329 |
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