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The Western Greece Soil Information System (WΕSIS)—A Soil Health Design Supported by the Internet of Things, Soil Databases, and Artificial Intelligence Technologies in Western Greece

Author

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  • Georgios Kalantzopoulos

    (Department of Agriculture, University of Patras, 26504 Patras, Greece)

  • Panagiotis Paraskevopoulos

    (Directorate of Agricultural Economy, Region of Western Greece, 26443 Patras, Greece
    Laboratory of Soil Science & Agricultural Chemistry, Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, 11855 Athens, Greece)

  • Georgios Domalis

    (Novelcore, Par. Theofrastou 140, 26443 Patras, Greece)

  • Aglaia Liopa-Tsakalidi

    (Department of Agriculture, University of Patras, 26504 Patras, Greece)

  • Dimitrios E. Tsesmelis

    (Department of Agriculture, University of Patras, 26504 Patras, Greece)

  • Pantelis E. Barouchas

    (Department of Agriculture, University of Patras, 26504 Patras, Greece)

Abstract

Soil quality is vital for ecosystem stability, impacting human, plant, and animal health. Traditional soil quality assessments are labor-intensive and costly, making them unsuitable for smart agriculture. To overcome this, Internet of Things (IoT) and artificial intelligence (AI) technologies are employed for sustainable agriculture, enabling real-time data collection and analysis, trend identification, and soil health optimization. The Western Greece Soil Information System (WΕSIS) offers open-access data and services for soil health and sustainability. It includes modules for soil quality indicators, sustainable fertilization management zones, soil property distribution, prediction, mapping, statistical analysis, water management, land use maps, digital soil mapping, and crop health calculation. Integrating the IoT and AI allows for real-time and remote monitoring of soil conditions, managing soil interventions adaptively and in a data-driven way, enhancing soil resources’ efficiency and sustainability, and increasing crop yield and quality. AI algorithms assist farmers and regional stakeholders in optimizing production lines, methodologies, and field practices, reducing costs and increasing profitability. This promotes a circular economy, a soil- and climate-resilient future, biodiversity protection targets, and enhanced soil fertility and productivity. The proposed IoT/AI technical architecture can underpin the development of soil health monitoring platforms, integrating data from various sources, automating data collection, and providing decision support tools.

Suggested Citation

  • Georgios Kalantzopoulos & Panagiotis Paraskevopoulos & Georgios Domalis & Aglaia Liopa-Tsakalidi & Dimitrios E. Tsesmelis & Pantelis E. Barouchas, 2024. "The Western Greece Soil Information System (WΕSIS)—A Soil Health Design Supported by the Internet of Things, Soil Databases, and Artificial Intelligence Technologies in Western Greece," Sustainability, MDPI, vol. 16(8), pages 1-18, April.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:8:p:3478-:d:1380019
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    References listed on IDEAS

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    1. Jun Liu & Haotian Cai & Shan Chen & Jie Pi & Liye Zhao, 2023. "A Review on Soil Nitrogen Sensing Technologies: Challenges, Progress and Perspectives," Agriculture, MDPI, vol. 13(4), pages 1-19, March.
    2. Bwambale, Erion & Abagale, Felix K. & Anornu, Geophrey K., 2022. "Smart irrigation monitoring and control strategies for improving water use efficiency in precision agriculture: A review," Agricultural Water Management, Elsevier, vol. 260(C).
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