Version 1
: Received: 7 September 2024 / Approved: 8 September 2024 / Online: 9 September 2024 (08:43:13 CEST)
How to cite:
Shalini, V. T.; Neware, R.; Kumari, T.; Kumar, M. Soil Health Management Using Artificial Intelligence for Smart Agriculture Systems. Preprints2024, 2024090605. https://doi.org/10.20944/preprints202409.0605.v1
Shalini, V. T.; Neware, R.; Kumari, T.; Kumar, M. Soil Health Management Using Artificial Intelligence for Smart Agriculture Systems. Preprints 2024, 2024090605. https://doi.org/10.20944/preprints202409.0605.v1
Shalini, V. T.; Neware, R.; Kumari, T.; Kumar, M. Soil Health Management Using Artificial Intelligence for Smart Agriculture Systems. Preprints2024, 2024090605. https://doi.org/10.20944/preprints202409.0605.v1
APA Style
Shalini, V. T., Neware, R., Kumari, T., & Kumar, M. (2024). Soil Health Management Using Artificial Intelligence for Smart Agriculture Systems. Preprints. https://doi.org/10.20944/preprints202409.0605.v1
Chicago/Turabian Style
Shalini, V. T., Tanvi Kumari and Mukesh Kumar. 2024 "Soil Health Management Using Artificial Intelligence for Smart Agriculture Systems" Preprints. https://doi.org/10.20944/preprints202409.0605.v1
Abstract
In the recent years, with the advent of Artificial Intelligence (AI) traditional methods have seen a significant transformation in the agriculture sector, especially in soil management. Soil management involves practices that maintains and improves the physical, chemical as well as the biological properties of the soil. Soil health management is essential for both the environmental conservation and sustainable agriculture production, ensuring the soil productivity and functional aspects associated with the ecosystem. Soil health management is one of the most important aspects of agriculture and food production, hence preserving and enhancing the soil health is an essential factor for supporting agriculture. Integration of Artificial Intelligence (AI) technologies with soil health management offers the potential to enhance agricultural sustainability, productivity, adapt to the climatic changes and resource constraints. The study of AI tools that can help improve soil health management by providing more accurate and efficient monitoring, analysis and decision-making capabilities. This paper studies the potential AI technologies including machine learning, robotics, and remote sensing in enhancing soil health, raising crop yields, and lowering environmental concerns by examining previous research and case studies.
Keywords
Artificial Intelligence; Soil Health; Deep Learning; Machine Learning; Unmanned Aerial Vehicle; ANN
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
