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Sustainable soil management is essential for ensuring food quality, environmental health and climate resilience. This systematic survey examines the evolution and integration of Artificial Intelligence (AI) and Machine Learning (ML) within green agricultural technologies aimed at enhancing soil health. This paper focuses on sensor networks, remote sensing, Internet of Things (IoT), robotics and data-driven decision-support systems to assess their efficiency in precision soil diagnostics, fertility management and resource conservation. While these green AI technologies show promising benefits, improved resource efficiency, reduced environmental footprint, regenerative soil practices challenges persist, including uneven soil data availability, high implementation costs and limited interpretability of models and lack of standardization.

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The Need for Sustainable AI-Based Green Technology for Soil Management in Agriculture

  • 会议论文

  • 发表日期：

    2026年

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  • S. Shalini,
  • A. Mamatha,
  • S. Sheela,
  • B. A. Mala,
  • Nagaraj M. Lutimath,
  • Koustav Biswas

摘要

Sustainable soil management is essential for ensuring food quality, environmental health and climate resilience. This systematic survey examines the evolution and integration of Artificial Intelligence (AI) and Machine Learning (ML) within green agricultural technologies aimed at enhancing soil health. This paper focuses on sensor networks, remote sensing, Internet of Things (IoT), robotics and data-driven decision-support systems to assess their efficiency in precision soil diagnostics, fertility management and resource conservation. While these green AI technologies show promising benefits, improved resource efficiency, reduced environmental footprint, regenerative soil practices challenges persist, including uneven soil data availability, high implementation costs and limited interpretability of models and lack of standardization.