The application of artificial intelligence (AI) in soil health assessment presents significant advancements over conventional methods by enabling more efficient and precise measurements. This review examines and supports how AI monitors soil health and its significance for sustainable land management. AI technologies, including machine learning, remote sensing and big data analytics, enable researchers and practitioners to analyse diverse data sources, model soil-plant relations and predict soil health trends with greater accuracy. AI-integrated soil health monitoring enables tracking of key soil parameters, facilitating efficient nutrient management, soil erosion control and overall ecosystem sustainability. AI-driven precision agriculture helps stakeholders predict the long-term impacts of farming practices, optimize resource use, enhance crop yields and reduce environmental impacts. This review also demonstrates how updated highlights recent research, case studies and best practices that demonstrate how AI-based soil health monitoring contributes to agricultural sustainability, conservation and food security.
Gayathri et al. (Sun,) studied this question.
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