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AI Solution for Farmers
Subject area: Science,Engineering and Technology · Area of research: Artificial Intelligence
Abstract
This AI solution addresses the challenges faced by farmers in optimizing crop selection based on soil quality parameters, specifically Nitrogen (N), Phosphorus (P), and Potassium (K), commonly known as NPK. The system integrates additional environmental factors such as temperature, humidity, and rainfall to provide a comprehensive analysis for informed decision-making in agriculture. By leveraging machine learning algorithms, the AI model analyzes historical and real-time data to assess the soil composition and environmental conditions, offering insights into the most suitable crops for cultivation. The target variable of this solution is the recommended crop for planting, taking into account the optimal NPK levels and environmental factors. This innovative approach empowers farmers with personalized recommendations, enhancing crop yield and sustainability while minimizing resource input. The AI solution serves as a valuable tool in modernizing agricultural practices, fostering efficiency, and contributing to the overall well-being of the farming community.
References
[1] M. A. Kekane, “Indian agriculture-status, importance and role in Indian economy”, International Journal of Agriculture and Food Science Technology, Vol. 4, No. 4, pp. 343-346, 2013
[2] B. F. Johnston, P. Kilby, Agriculture and Structural Transformation: Economic Strategies in Late-Developing Countries, Oxford University Press, 1975
[3] S. Kuznets, “Modern economic growth: Findings and reflections”, American Economic Association, Vol. 63, No. 3, pp. 247–258, 1973
[4] M. Syrquin, “Patterns on Structural Change”, in: Handbook of Development Economics, Vol. 1, Elsevier, 1988
[5] R. Dekle, G. Vandenbroucke, “A quantitative analysis of China’s structural transformation”, Journal of Economic Dynamics and Control, Vol. 36, No. 1, pp. 119-135, 2012
[6] M. Fan, J.Shen, L. Yuan, R. Jiang, X. Chen, W. J. Davies, F. Zhang, “Improving crop productivity and resource use efficiency to ensure food security and environmental quality in China”, Journal of Experimental Botany, Vol. 63, No. 1, pp. 13-24, 2012
How to cite this paper
@article{1705379,
author = {Ashok D S, C Venkateswara Reddy, R D Aditya, TDV Karthik, Prof P Peniel John Whistly},
title = {AI Solution for Farmers},
journal = {Iconic Research And Engineering Journals},
year = {2024},
volume = {7},
number = {7},
pages = {139-143},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1705379.pdf},
abstract = {This AI solution addresses the challenges faced by farmers in optimizing crop selection based on soil quality parameters, specifically Nitrogen (N), Phosphorus (P), and Potassium (K), commonly known as NPK. The system integrates additional environmental factors such as temperature, humidity, and rainfall to provide a comprehensive analysis for informed decision-making in agriculture. By leveraging machine learning algorithms, the AI model analyzes historical and real-time data to assess the soil composition and environmental conditions, offering insights into the most suitable crops for cultivation. The target variable of this solution is the recommended crop for planting, taking into account the optimal NPK levels and environmental factors. This innovative approach empowers farmers with personalized recommendations, enhancing crop yield and sustainability while minimizing resource input. The AI solution serves as a valuable tool in modernizing agricultural practices, fostering efficiency, and contributing to the overall well-being of the farming community.},
month = {January},
}